Humans have a remarkable capacity for coordination. Our ability to interact and act jointly in groups is crucial to our success as a species. Joint Action (JA) research has often concerned itself with simplistic behaviors in highly constrained laboratory tasks. But there has been a growing interest in understanding complex coordination in more open-ended contexts. In this regard, collective music improvisation has emerged as a fascinating model domain for studying basic JA mechanisms in an unconstrained and highly sophisticated setting. A number of empirical studies have begun to elucidate coordination mechanisms underlying joint musical improvisation, but these findings have yet to be cached out in a working computational model. The present work fills this gap by presenting Tonal Emergence, an idealized agent-based model of improvised musical coordination. Tonal Emergence models the coordination of notes played by improvisers to generate harmony (i.e., tonality), by simulating agents that stochastically generate notes biased towards maximizing harmonic consonance given their partner’s previous notes. The model replicates an interesting empirical result from a previous study of professional jazz pianists: feedback loops of mutual adaptation between interacting agents support the production of consonant harmony. The model is further explored to show how complex tonal dynamics, such as the production and dissolution of stable tonal centers, are supported by agents that are characterized by (i) a tendency to strive toward consonance, (ii) stochasticity, and (iii) a limited memory for previously played notes. Tonal Emergence thus provides a grounded computational model to simulate and probe the coordination mechanisms underpinning one of the more remarkable feats of human cognition: collective music improvisation.
Often members of a group benefit from dividing the group’s task into separate components, where each member specializes their role so as to accomplish only one of the components. While this division of labor phenomenon has been observed with respect to both manual and cognitive labor, there is no clear understanding of the cognitive mechanisms allowing for its emergence, especially when there are multiple divisions possible and communication is limited. Indeed, maximization of expected utility often does not differentiate between alternative ways in which individuals could divide labor. We developed an iterative two-person game in which there are multiple ways of dividing labor, but in which it is not possible to explicitly negotiate a division. We implemented the game both as a human experimental task and as a computational model. Our results show that the majority of human dyads can finish the game with an efficient division of labor. Moreover, we fitted our computational model to the behavioral data, which allowed us to explain how the perceived similarity between a player’s actions and the task’s focal points guided the players’ choices from one round to the other, thus bridging the group dynamics and its underlying cognitive process. Potential applications of this model outside cognitive science include the improvement of cooperation in human groups, multi-agent systems, as well as human-robot collaboration.
Tump, A. N., Wu, C. M., Bouhlel, I., & Goldstone, R. L. (2019).The Evolutionary Dynamics of Cooperation in Collective Search. Proceedings of the 41st Annual Conference of the Cognitive Science Society. (pp. 883-889). Montreal, Canada: Cognitive Science Society.
How does cooperation arise in an evolutionary context? We approach this problem using a collective search paradigm where interactions are dynamic and there is competition for rewards. Using evolutionary simulations, we find that the unconditional sharing of information can be an evolutionary advantageous strategy without the need for conditional strategies or explicit reciprocation. Shared information acts as a recruitment signal and facilitates the formation of a self-organized group. Thus, the improved search efficiency of the collective bestows byproduct benefits onto the original sharer. A key mechanism is a visibility radius, where individuals have unconditional access to information about neighbors within a limited distance. Our results show that for a variety of initial conditions—including populations initially devoid of prosocial individuals—and across both static and dynamic fitness landscapes, we find strong selection pressure to evolve unconditional sharing.
Setzler, M., & Goldstone, R. L. (2019). Patterns of coordination in simultaneously and sequentially improvising jazz musicians. Proceedings of the 41st Annual Conference of the Cognitive Science Society. (pp. 1035-1040). Montreal, Canada: Cognitive Science Society.
In Joint Action (JA) tasks, individuals must coordinate their actions so as to achieve some desirable outcome at the grouplevel. Group function is an emergent outcome of ongoing, mutually constraining interactions between agents. Here we investigate JA in dyads of improvising jazz pianists. Participants’ musical output is recorded in one of two conditions: a real condition, in which two pianists improvise together as they typically would, and a virtual condition, in which a single pianist improvises along with a “ghost partner” – a recording of another pianist taken from a previous real trial. The conditions are identical except for that in real trials subjects are mutually coupled to one another, whereas there is only unidirectional influence in virtual trials (i.e. recording to musician). We quantify ways in which the rhythmic structures spontaneously produced in these improvisations is shaped by mutual coupling of co-performers. Musical signatures of underlying coordination patterns are also shown to parallel the subjective experience of improvisers, who preferred playing in trials with bidirectional influence despite not explicitly knowing which condition they had played in. These results illuminate how mutual coupling shapes emergent, group-level structure in the creative, open-ended and fundamentally collaborative domain of expert musical improvisation.
Sloman, S. J., Goldstone, R. L., & Gonzalez, C. (2019). Complex exploration dynamics from simple heuristics in a collective learning environment. Proceedings of the 41st Annual Conference of the Cognitive Science Society. (pp. 2818-2824). Montreal, Canada: Cognitive Science Society.
Effective problem solving requires both exploration and exploitation. We analyze data from a group problem-solving task to gain insight into how people use information from past experiences and from others to achieve explore-exploit trade-offs in complex environments. The behavior we observe is consistent with the use of simple, reinforcement-based heuristics. Participants increase exploration immediately after experiencing a low payoff, and decrease exploration immediately after experiencing a high or improved payoff. We suggest that whether an outcome is perceived as “high” or “low” is a dynamic function of the outcome information available to participants. The degree to which the distribution of observed information reflects the true range of possible outcomes plays an important role in determining whether or not this heuristic is adaptive in a given environment.
Andrade-Lotero, E., & Goldstone, R. L. (2019). Self-Organized Division of Cognitive Labor. Proceedings of the 41st Annual Conference of the Cognitive Science Society. (pp. 91-97). Montreal, Canada: Cognitive Science Society.
The division of labor phenomenon has been observed with respect to both manual and cognitive labor, but there is no clear understanding of the intra- and inter-individual mechanisms that allow for its emergence, especially when there are multiple divisions possible and communication is limited. Situations fitting this description include individuals in a group splitting a geographical region for resource harvesting without explicit negotiation, or a couple tacitly negotiating the hour of the day for each to shower so that there is sufficient hot water. We studied this phenomenon by means of an iterative two-person game where multiple divisions are possible, but no explicit communication is allowed. Our results suggest that there are a limited number of biases toward divisions of labor, which serve as attractors in the dynamics of dyadic coordination. However, unlike Schelling’s focal points, these biases do not attract players’ attention at the onset of the interaction, but are only revealed and consolidated by the in-game dynamics of dyadic interaction.
The utility of our actions frequently depends upon the beliefs and behavior of other agents. Thankfully, through experience, we learn norms and conventions that provide stable expectations for navigating our social world. Here, we review several distinct influences on their content and distribution. At the level of individuals locally interacting in dyads, success depends on rapidly adapting pre-existing norms to the local context. Hence, norms are shaped by complex cognitive processes involved in learning and social reasoning. At the population level, norms are influenced by intergenerational transmission and the structure of the social network. As human social connectivity continues to increase, understanding and predicting how these levels and time scales interact to produce new norms will be crucial for improving communities.
Low-level “adaptive” and higher-level “sophisticated” human reasoning processes have been proposed to play opposing roles in the emergence of unpredictable collective behaviors such as crowd panics, traffic jams, and market bubbles. While adaptive processes are widely recognized drivers of emergent social complexity, complementary theories of sophistication predict that incentives, education, and other inducements to rationality will suppress it. We show in a series of multiplayer laboratory experiments that, rather than suppressing complex social dynamics, sophisticated reasoning processes can drive them. Our experiments elicit an endogenous collective behavior and show that it is driven by the human ability to recursively anticipate the reasoning of others. We identify this behavior, “sophisticated flocking”, across three games, the Beauty Contest and the “Mod Game” and “Runway Game”. In supporting our argument, we also present evidence for mental models and social norms constraining how players express their higher-level reasoning abilities. By implicating sophisticated recursive reasoning in the kind of complex dynamic that it has been predicted to suppress, we support interdisciplinary perspectives that emergent complexity is typical of even the most intelligent populations and carefully designed social systems.
McColeman, C., Michal, A., Goldstone, R. l., Schloss, K., Kaminski, J., & Hullman, J. (2018). Data visualization as a domain to research areas in cognitive science. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pp. 35-36). Madison, Wisconsin: Cognitive Science Society.
How people are able to turn information in the environment into meaning is a critical question for cognitive science. That environment is increasingly data-driven. Using data to inform decisions and improve understanding of the world is a valuable component of critical thinking, and serves as the foundation of evidence-based decision making. Designing graphical representations can make those data more accessible, such that users may engage the visual system and capacity for visual pattern recognition to discern regularities and properties of data. We ultimately want to understand the connection between the initial perception of data visualizations and conceptual understanding of information. Data visualizations, broadly, are the representation of recorded values in visual form, including scientific visualizations such as brain scans, or live visualizations such as stock market monitoring; the work discussed through this symposium is of the type used in science, business, and medical settings to display data abstractly.
Bouhlel, I., Wu, C. M., Hanaki, N., & Goldstone, R. L. (2018). Sharing is not erring: Pseudo-reciprocity in collective search. Proceedings of the 40th Annual Conference of the Cognitive Science Society. (pp. 156-161). Madison, Wisconsin: Cognitive Science Society.
Information sharing in competitive environments may seem counterintuitive, yet it is widely observed in humans and other animals. For instance, the open-source software movement has led to new and valuable technologies being released publicly to facilitate broader collaboration and further innovation. What drives this behavior and under which conditions can it be beneficial for an individual? Using simulations in both static and dynamic environments, we show that sharing information can lead to individual benefits through the mechanisms of pseudoreciprocity, whereby shared information leads to by-product benefits for an individual without the need for explicit reciprocation. Crucially, imitation with a certain level of innovation is required to avoid a tragedy of the commons, while the mechanism of a local visibility radius allows for the coordination of self-organizing collectives of agents. When these two mechanisms are present, we find robust evidence for the benefits of sharing—even when others do not reciprocate.
We lay out a multiple, interacting levels of cognitive systems (MILCS) framework to account for the cognitive capacities of individuals and the groups to which they belong. The goal of MILCS is to explain the kinds of cognitive processes typically studied by cognitive scientists, such as perception, attention, memory, categorization, decision-making, problem solving, judgment, and flexible behavior. Two such systems are considered in some detail—lateral inhibition within a network for selecting the most attractive option from a candidate set and a diffusion process for accumulating evidence to reach a rapid and accurate decision. These system descriptions are aptly applied at multiple levels, including within and across people. These systems provide accounts that unify cognitive processes across multiple levels, can be expressed in a common vocabulary provided by network science, are inductively powerful yet appropriately constrained, and are applicable to a large number of superficially diverse cognitive systems. Given group identification processes, cognitively resourceful people will frequently form groups that effectively employ cognitive systems at higher levels than the individual. The impressive cognitive capacities of individual people do not eliminate the need to talk about group cognition. Instead, smart people can provide the interacting parts for smart groups
An individual can interact with the same set of people over many different scales simultaneously. Four people might interact as a group of four and, at the same time, in pairs and triads. What is the relationship between different parallel interaction scales, and how might those scales themselves interact? We devised a four-player experimental game, the Modular Stag Hunt, in which participants chose not just whether to coordinate, but with whom, and at what scale. Our results reveal coordination behavior with such a strong preference for dyads that undermining pairwise coordination actually improves group-scale outcomes. We present these findings as experimental evidence for competition, as opposed to complementarity, between different possible scales of multi-player coordination. This result undermines a basic premise of approaches, like those of network science, that fail to model the interacting effects of dyadic, triadic, and group-scale structure on group outcomes.
To investigate the effect of competitive incentives under peer review, we designed a novel experimental setup called the Art Exhibition Game. We present experimental evidence of how competition introduces both positive and negative effects when creative artifacts are evaluated and selected by peer review. Competition proved to be a double-edged sword: on the one hand, it fosters innovation and product diversity, but on the other hand, it also leads to more unfair reviews and to a lower level of agreement between reviewers. Moreover, an external validation of the quality of peer reviews during the laboratory experiment, based on 23,627 online evaluations on Amazon Mechanical Turk, shows that competition does not significantly increase the level of creativity. Furthermore, the higher rejection rate under competitive conditions does not improve the average quality of published contributions, because more high-quality work is also rejected. Overall, our results could explain why many ground-breaking studies in science end up in lower-tier journals. Differences and similarities between the Art Exhibition Game and scholarly peer review are discussed and the implications for the design of new incentive systems for scientists are explained.
[This paper is a commentary on the following article: Gintis, H., & Helbing, D. (2015). Homo Socialis: An Analytical Core for Sociological Theory. Review of Behavioral Economics.]
Explaining how patterns of collective behavior emerge from interactions among individuals with diverse, sometimes opposing, goals is a societally crucial and particularly timely pursuit. It is timely because humans are more tightly connected to one another now than ever before. From 1984 to 2014 there has been more than a million-fold increase in the number of devices that can reach the global digital network. Although web technology is new and transformative, from a broader perspective, it is also just a recent manifestation of humanity’s perpetual drive to become more intermeshed. Earlier manifestations of this drive include the printing press, global transportation networks, telecommunication systems, and the academy. These social networks have catalyzed the formation of otherwise unattainable social patterns. Understanding the origins and possible destinations of these social patterns is both scientifically and pragmatically consequential.
Leydesdorff, L., & Goldstone, R. L. (2014). Interdisciplinarity at the Journal and Specialty Level: The changing knowledge bases of the journal Cognitive Science. Journal of the American Society for Information Science and Technology, 65, 164-177.
Using the referencing patterns in articles in Cognitive Science over three decades, we analyze the knowledge base of this literature in terms of its changing disciplinary composition. Three periods are distinguished: (1) construction of the interdisciplinary space in the 1980s; (2) development of an interdisciplinary orientation in the 1990s; (3) reintegration into “cognitive psychology” in the 2000s. The fluidity and fuzziness of the interdisciplinary delineations in the different visualizations can be reduced and clarified using factor analysis. We also explore newly available routines (“CorText”) to analyze this development in terms of “tubes” using an alluvial map, and compare the results with an animation (using “visone”). The historical specificity of this development can be compared with the development of “artificial intelligence” into an integrated specialty during this same period. “Interdisciplinarity” should be defined differently at the level of journals and of specialties.
Here are some reports of our PLoS One paper on human collective behavior studying cyclic patterns in a generalization of the familiar rock-scissors-paper game. We find situations in which groups of people grow increasingly predictable as they cycle around a set of choice options in a game similar to rock-scissors-paper but with 24 rather than 3 choices.
When making decisions, humans can observe many kinds of information about others’ activities, but their effects on performance are not well understood. We investigated social learning strategies using a simple problem-solving task in which participants search a complex space, and each can view and imitate others’ solutions. Results showed that participants combined multiple sources of information to guide learning, including payoffs of peers’ solutions, popularity of solution elements among peers, similarity of peers’ solutions to their own, and relative payoffs from individual exploration. Furthermore, performance was positively associated with imitation rates at both the individual and group levels. When peers’ payoffs were hidden, popularity and similarity biases reversed, participants searched more broadly and randomly, and both quality and equity of exploration suffered. We conclude that when peers’ solutions can be effectively compared, imitation does not simply permit scrounging, but it can also facilitate propagation of good solutions for further cumulative exploration.
Recent theories from complexity science argue that complex dynamics are ubiquitous in social and economic systems. These claims emerge from the analysis of individually simple agents whose collective behavior is surprisingly complicated. However, economists have argued that iterated reasoning–what you think I think you think–will suppress complex dynamics by stabilizing or accelerating convergence to Nash equilibrium. We report stable and efficient periodic behavior in human groups playing the Mod Game, a multi-player game similar to Rock-Paper-Scissors. The game rewards subjects for thinking exactly one step ahead of others in their group. Groups that play this game exhibit cycles that are inconsistent with any fixed-point solution concept. These cycles are driven by a ‘‘hopping’’ behavior that is consistent with other accounts of iterated reasoning: agents are constrained to about two steps of iterated reasoning and learn an additional one-half step with each session. If higher-order reasoning can be complicit in complex emergent dynamics, then cyclic and chaotic patterns may be endogenous features of real-world social and economic systems.
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See a movie of actual humans (shown as Xs) playing the Mod Game. Notice the clumping of their moves and their regular progression around the circle of choices.
Unlike how most psychology experiments on learning operate, people learning to do a task typically do so in the context of other people learning to do the same task. In these situations, people take advantage of others’ solutions, and may modify and extend these solutions, thereby affecting the solutions available to others. We are interested in the group patterns that emerge when people can see and imitate the solutions, innovations, and choices of their peers over several rounds. In one series of experiments and computer simulations, we find that there is a systematic relation between the difficulty of a problem search space and the optimal social network for transmitting solutions. As the difficulty of finding optimal solutions in a search space increases, communication networks that preserve spatial neighborhoods perform best. Restricting people’s access to others’ solutions can help the group as a whole find good, hard-to-discover solutions. In other experiments with more complex search spaces, we find evidence for several heuristics governing individuals’ decisions to imitate: imitating prevalent options, imitating options that become increasingly prevalent, imitating high-scoring options, imitating during the early stages of a multiround search process, and imitating solutions similar to one’s own solution. Individuals who imitate tend to perform well, and more surprisingly, individuals also perform well when they are in groups with other individuals who imitate frequently. Taken together, our experiments on collective social learning reveal laboratory equivalents of prevalent social phenomena such as bandwagons, strategy convergence, inefficiencies in the collective coverage of a problem space, social dilemmas in exploration/exploitation, and reciprocal imitation.
Weitnauer, E., Carvalho, P. F., Goldstone, R. L., & Ritter, H. (2013). Grouping by Similarity Helps Concept Learning. Proceedings of the Thirty-Fifth Annual Conference of the Cognitive Science Society. (pp. 3747-3752). Berlin, Germany: Cognitive Science Society.
In inductive learning, the order in which concept instances are presented plays an important role in learning performance. Theories predict that interleaving instances of different concepts is especially beneficial if the concepts are highly similar to each other, whereas blocking instances belonging to the same concept provides an advantage for learning lowsimilarity concept structures. This leaves open the question of the relative influence of similarity on interleaved versus blocked presentation. To answer this question, we pit withinand between-category similarity effects against each other in a rich categorization task called Physical Bongard Problems. We manipulate the similarity of instances shown temporally close to each other with blocked and interleaved presentation. The results indicate a stronger effect of similarity on interleaving than on blocking. They further show a large benefit of comparing similar between-category instances on concept learning tasks where the feature dimensions are not known in advance but have to be constructed.
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We implemented a problem-solving task in which groups of participants simultaneously played a simple innovation game in a complex problem space, with score feedback provided after each of a number of rounds. Each participant in a group was allowed to view and imitate the guesses of others during the game. The results showed the use of social learning strategies previously studied in other species, and demonstrated benefits of social learning and nonlinear effects of group size on strategy and performance. Rather than simply encouraging conformity, groups provided information to each individual about the distribution of useful innovations in the problem space. Imitation facilitated innovation rather than displacing it, because the former allowed good solutions to be propagated and preserved for further cumulative innovations in the group. Participants generally improved their solutions through the use of fairly conservative strategies, such as changing only a small portion of one’s solution at a time, and tending to imitate solutions similar to one’s own. Changes in these strategies over time had the effect of making solutions increasingly entrenched, both at individual and group levels. These results showed evidence of nonlinear dynamics in the decentralization of innovation, the emergence of group phenomena from complex interactions of individual efforts, stigmergy in the use of social information, and dynamic tradeoffs between exploration and exploitation of solutions. These results also support the idea that innovation and creativity can be recognized at the group level even when group members are generally cautious and imitative.
Frey, S., & Goldstone, R. L. (2011). Going with the group in a competitive game of iterated reasoning. Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society. (pp. 1912-1917). Boston, Massachusetts: Cognitive Science Society.
In some strategic games, thinking ahead about other players’ reasoning can lead to better predictions about what they will do. In other games, infinitely iterated reasoning ultimately prescribes random play. In an online experiment of strategic thinking in groups, we tested participants in a game with the formal structure of a random game, but the superficial struc- ture of a game that rewards iterated reasoning. We found that participants conformed to the superficial structure of the game, and earned more than they would have by playing randomly. We estimated how many steps participants thought ahead in the game and discovered implicit coordination at the group level. Participants unexpectedly “matched” their degree of iterated thinking to each other.
Roberts, M. E., & Goldstone, R. L. (2011). Adaptive Group Coordination and Role Differentiation. PLoS One, 6, 1-8.
Many real world situations (potluck dinners, academic departments, sports teams, corporate divisions, committees, seminar classes, etc.) involve actors adjusting their contributions in order to achieve a mutually satisfactory group goal, a win-win result. However, the majority of human group research has involved situations where groups perform poorly because task constraints promote either individual maximization behavior or diffusion of responsibility, and even successful tasks generally involve the propagation of one correct solution through a group. Here we introduce a group task that requires complementary actions among participants in order to reach a shared goal. Without communication, group members submit numbers in an attempt to collectively sum to a randomly selected target number. After receiving group feedback, members adjust their submitted numbers until the target number is reached. For all groups, performance improves with task experience, and group reactivity decreases over rounds. Our empirical results provide evidence for adaptive coordination in human groups, and as the coordination costs increase with group size, large groups adapt through spontaneous role differentiation and self-consistency among members. We suggest several agent-based models with different rules for agent reactions, and we show that the empirical results are best fit by a flexible, adaptive agent strategy in which agents decrease their reactions when the group feedback changes. The task offers a simple experimental platform for studying the general problem of group coordination while maximizing group returns, and we distinguish the task from several games in behavioral game theory.
Day, S. B., Manlove, S., & Goldstone, R. L. (2011). Transfer, and the effects of context outside of the training task. Proceedings of the Thirty-Third Annual Conference of the Cognitive Science Society. (pp. 2637-2642). Boston, Massachusetts: Cognitive Science Society.
While the use of concrete, contextualized and personally relevant examples can benefit learners in terms of comprehension and motivation, these types of examples can come with a cost. Examples may become too bound to their particular context, and individuals may have a difficult time recognizing when the underlying principles are relevant in new situations. In the current study, we provide evidence that contextualization may impair knowledge transfer even when that context occurs outside of the training example itself. Specifically, when students were taught about positive feedback systems in the context of polar ice-albedo effects, those individuals that had previously learned about the effects of global warming on polar bear populations showed reliably poorer transfer performance.
Frey, S., & Goldstone, R. L. (2010). Functional Structure and Coordination Failure in Real-Time Group Behavior. Proceedings of the Thirty-Second Annual Conference of the Cognitive Science Society. (pp. 2093-2098). Portland, Oregon: Cognitive Science Society.
We reveal spontaneous group formation and differentiation in an online dynamic coordination experiment. We observe increased group stratification and attribute it to increases in pairwise cooperative behavior, rather than uncooperative behavior. Our network analyses document the fine scale structure of coordination failure in the face of many established determinants of coordination success. We explore previous work in coordination failure to frame our own findings. Factors that have been previously shown to improve coordination in discretetime, forced-decision experimental games do not prevent decisive coordination failure in our real-time, asynchronous group decision-making environment.
Goldstone, R. L., Landy, D. H., & Son, J. Y. (2010). The education of perception. Topics in Cognitive Science, 2, 265-284.
While the field of perceptual learning has mostly been concerned with low- to middle-level changes to perceptual systems due to experience, we consider high-level perceptual changes that accompany learning in science and mathematics. In science, we explore the transfer of a scientific principle (competitive specialization) across superficially dissimilar pedagogical simulations. We argue that transfer occurs when students develop perceptual interpretations of an initial simulation and simply continue to use the same interpretational bias when interacting with a second simulation. In arithmetic and algebraic reasoning, we find that proficiency in mathematics involves executing spatially explicit transformations to notational elements. People learn to attend mathematical operations in the order in which they should be executed, and the extent to which students employ their perceptual attention in this manner is positively correlated with their mathematical experience. For both science and mathematics, relatively sophisticated performance is achieved not by ignoring perceptual features in favor of deep conceptual features, but rather by adapting perceptual processing so as to conform with and support formally sanctioned responses. These “Rigged Up Perceptual Systems” (RUPS) offer a promising approach to educational reform.
Hills, T. T., Todd, P. M., & Goldstone, R. L. (2010). Priming a Central Executive Search Process: Exploration and Exploitation in Generalized Cognitive Search Processes. Journal of Experimental Psychology: General, 139, 560-609.
The trade-off between exploration and exploitation is common to a wide variety of problems involving search in space and mind. The prevalence of this trade-off and its neurological underpinnings led us to propose domain-general cognitive search processes (Hills, Todd, & Goldstone, 2008). We propose further that these are consistent with the idea of a central executive search process that combines goal-handling across subgoal hierarchies. In the present study, we investigate 3 aspects of this proposal. First, the existence of a unitary central executive search process should allow priming from 1 search task to another and at multiple hierarchical levels. We confirm this by showing cross-domain priming from a spatial search task to 2 different cognitive levels within a lexical search task. Second, given the neural basis of the proposed generalized cognitive search process and the evidence that the central executive is primarily engaged during complex tasks, we hypothesize that priming should require search in the sense of a self-regulated making and testing of sequential predictions about the world. This was confirmed by showing that when participants were allowed to collect spatial resources without searching for them, no priming occurred. Finally, we provide a mechanism for the underlying search process and investigate 3 alternative hypotheses for subgoal hierarchies using the central executive as a search process model (CESP). CESP envisions the central executive as having both emergent and unitary processes, with one of its roles being a generalized cognitive search process that navigates goal hierarchies by mediating persistence on and switching between subgoals.
Theiner, G, Allen, C., & Goldstone, R. L. (2010). Recognizing group cognition. Cognitive Systems Research, 11, 378-395.
In this paper, we approach the idea of group cognition from the perspective of the ”extended mind” thesis, as a special case of the more general claim that systems larger than the individual human, but containing that human, are capable of cognition (Clark, 2008; Clark & Chalmers, 1998). Instead of deliberating about ”the mark of the cognitive” (Adams & Aizawa, 2008), our discussion of group cognition is tied to particular cognitive capacities. We review recent studies of group problem solving and group memory which reveal that specific cognitive capacities that are commonly ascribed to individuals are also aptly ascribed at the level of groups. These case studies show how dense interactions among people within a group lead to both similarity-inducing and differentiating dynamics that affect the group’s ability to solve problems. This supports our claim that groups have organization-dependent cognitive capacities that go beyond the simple aggregation of the cognitive capacities of individuals. Group cognition is thus an emergent phenomenon in the sense of Wimsatt (1986). We further argue that anybody who rejects our strategy for showing that cognitive properties can be instantiated at multiple levels in the organizational hierarchy on a priori grounds is a ”demergentist,” and thus incurs the burden of proof for explaining why cognitive properties are ”stuck” at a certain level of organizational structure. Finally, we show that our analysis of group cognition escapes the ”coupling-constitution” charge that has been leveled against the extended mind thesis (Adams & Aizawa, 2008).
Gureckis, T. M., & Goldstone, R. L. (2009). How you named your child: Understanding the relationship between individual decision-making and collective outcomes. Topics in Cognitive Science, 1, 651-674.
We examine the interdependence between individual and group behavior surrounding a somewhat arbitrary, real world decision: selecting a name for
one’s child. Using a historical database of the names given to children over the last century in the United States, we nd that naming choices are influenced by both the frequency of a name in the general population, and by its “momentum” in the recent past in the sense that names which are growing in popularity are preferentially chosen. This bias toward rising names is a recent phenomena: in the early part of the 20th century, increasing popularity of a name from one time period to the next was correlated with a decrease in future popularity. However, more recently this trend has reversed. We evaluate a number of formal models that detail how individual decision-making strategies, played out in a large population of interacting agents, can explain these empirical observations. We argue that cognitive capacities for change detection, the encoding of frequency in memory, and biases towards novel or incongruous stimuli may interact with the behavior of other decision makers to determine the distribution and dynamics of cultural tokens such as names.
Goldstone, R. L. & Gureckis, T. M. (2009). Collective behavior. Topics in Cognitive Science, 1, 412-438.
The resurgence of interest in collective behavior is in large part due to tools recently made available for conducting laboratory experiments on groups, statistical methods for analyzing large data sets reflecting social interactions, the rapid growth of a diverse variety of online self-organized collectives, and computational modeling methods for understanding both universal and scenario-specific social patterns. We consider case studies of collective behavior along four attributes: the primary motivation of individuals within the group, kinds of interactions among individuals, typical dynamics that result from these interactions, and characteristic outcomes at the group level. With this framework, we compare the collective patterns of noninteracting decision makers, bee swarms, groups forming paths in physical and abstract spaces, sports teams, cooperation and competition for resource usage, and the spread and extension of innovations in an online community. Some critical issues surrounding collective behavior are then reviewed, including the questions of ‘‘Does group behavior always reduce to individual behavior?’’ ‘‘Is ‘group cognition’ possible?’’ and ‘‘What is the value of formal modeling for understanding group behavior?’’
Roberts, M. E., & Goldstone, R. L. (2009). Adaptive group coordination, Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society. 2698-2704. Amsterdam, Netherlands: Cognitive Science Society.
Human groups exhibit poor performance in many social situations because task constraints promote either individual maximization behavior or diffusion of responsibility. We introduce a group task that tests human coordination when only a shared group goal exists. Without communication, group members submit numbers in an attempt to collectively sum to a randomly selected number. After receiving group feedback, members adjust their submitted numbers in the next round. Small groups generally outperform large groups, and for all groups, performance improves with task experience, and reactivity to feedback decreases over rounds. Our empirical results and computational modeling provide evidence for adaptive coordination in human groups despite minimal shared history and only indirect communication, and perhaps most interestingly, as the coordination costs increase with group size, large groups adapt through spontaneous role differentiation and self-consistency among members.
Roberts, M. E., & Goldstone, R. L. (2009). Sub-optimalities in group foraging and resource competition. , Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society 2371-2377. Amsterdam, Netherlands: Cognitive Science Society.
Previous group foraging research has shown that human groups sub-optimally distribute themselves to resources and display undermatching, with a smaller-than-expected proportion of individuals at the more abundant resource pool. In order to further explore these sub-optimalities, we extended a group foraging paradigm to test three variables: the effects of three resource pools, travel cost between pools, and the size of the pools. Although each condition led to undermatching, the conditions showed significant differences in the extent of undermatching, the frequency of switching between resource pools, the wealth inequality among foragers, and the comparative wealth inequality at different resource pools. The results for the three pool conditions suggest that human groups have difficulty in discriminating the relative value of resource pools. The results for the travel cost conditions indicate that human groups distribute themselves to resources more optimally when individuals can easily switch between pools, which is the opposite of the result found with foraging pigeons. Finally, the results for the pool size conditions indicate that larger pool sizes promote greater undermatching, apparently because individuals inefficiently compete over large areas rather than effectively parceling the pools into smaller, distinct regions.
Son, J. Y., & Goldstone, R. L. (2009). Fostering General Transfer with Specific Simulations.Pragmatics and Cognition, 17, 1-42.
Science education faces the difficult task of helping students understand and appropriately generalize scientific principles across a variety of superficially dissimilar specific phenomena. Can cognitive technologies be adapted to benefit both learning specific domains and generalizable transfer? This issue is examined by teaching students complex adaptive systems with computer-based simulations. With a particular emphasis on fostering understanding that transfers to dissimilar phenomena, the studies reported here examine the influence of different descriptions and perceptual instantiations of the scientific principle of competitive specialization. Experiment 1 examines the role of intuitive descriptions to concrete ones, finding that intuitive descriptions leads to enhanced domain-specific learning but also deters transfer. Experiment 2 successfully alleviated these difficulties by combining intuitive descriptions with idealized graphical elements. Experiment 3 demonstrates that idealized graphics are more effective than concrete graphics even when unintuitive descriptions are applied to them. When graphics are concrete, learning and transfer largely depends on the particular description. However, when graphics are idealized, a wider variety of descriptions results in levels of learning and transfer similar to the best combination involving concrete graphics. Although computer-based simulations can be effective for learning that transfers, designing effective simulations requires an understanding of concreteness and idealization in both the graphical interface and its description.
Goldstone, R. L., & Wilensky, U. (2008). Promoting Transfer through Complex Systems Principles. Journal of the Learning Sciences, 17, 465-516.
Understanding scientific phenomena in terms of complex systems principles is both scientifically and pedagogically important. Situations from different disciplines of science are often governed by the same principle, and so promoting knowledge transfer across disciplines makes valuable cross-fertilization and scientific unification possible. Although evidence for this kind of transfer has been historically controversial, experiments and observations of students suggest pedagogical methods to promote transfer of complex systems principles. One powerful strategy is for students to actively interpret the elements and interactions of perceptually grounded scenarios. Such interpretation can be facilitated through the presentation of cases alongside general principles, and by students exploring and constructing computational models of cases. The resulting knowledge can be both concretely grounded yet highly perspective-dependent and generalizeable. We discuss methods for coordinating computational and mental models of complex systems, the roles of idealization and concreteness in fostering understanding and generalization, and other complementary theoretical approaches to transfer.
Goldstone, R. L., Roberts, M. E., & Gureckis, T. M. (2008). Emergent Processes in Group Behavior. Current Directions in Psychological Science, 17, 10-15.
Just as networks of neurons create structured thoughts beyond the ken of any individual neuron, so people spontaneously organize themselves into groups to create emergent organizations that no individual may intend, comprehend, or even perceive. Recent technological advances have provided us with unprecedented opportunities for conducting controlled, laboratory experiments on human collective behavior. We describe two experimental paradigms where we attempt to build predictive bridges between the beliefs, goals, and cognitive capacities of individuals and group-level patterns, showing how the members of a group dynamically allocate themselves to resources, and how innovations are spread in a social network. Agent-based computational models have provided useful explanatory and predictive accounts. Together, the models and experiments point to tradeoffs between exploration and exploitation, compromises between individuals using their own innovations and innovations obtained from their peers, and the emergence of group-level organizations such as population waves, bandwagon effects, and spontaneous specialization.
Mason, W. A., Jones, A., & Goldstone, R. L. (2008). Propagation of innovations in networked groups. Journal of Experimental Psychology: General, 137, 422-433.
A novel paradigm was developed to study the behavior of groups of networked people searching a problem space. We examined how different network structures affect the propagation of information in laboratory-created groups. Participants made numerical guesses and received scores that were also made available to their neighbors in the network. The networks were compared on speed of discovery and convergence on the optimal solution. One experiment showed that individuals within a group tend to converge on similar solutions even when there is an equally valid alternative solution. Two additional studies demonstrated that the optimal network structure depends on the problem space being explored, with networks that incorporate spatially-based cliques having an advantage for problems that benefit from broad exploration, and networks with greater long-range connectivity having an advantage for problems requiring less exploration.
Gureckis, T. M., & Goldstone, R. L. (2006). Thinking in groups. Pragmatics and Cognition, 14, 293-311
Is cognition an exclusive property of the individual or can groups have a mind of their own? We explore this question from the perspective of complex adaptive systems. One of the principle insights from this line of work is that rules that govern behavior at one level of analysis (the individual) can cause qualitatively different behavior at higher levels (the group). We review a number of behavioral studies from our lab that demonstrate how groups of people interacting in real-time can self-organize into adaptive, problem-solving group structures. A number of principles are derived concerning the critical features of such “distributed” information processing systems. We suggest that while cognitive science has traditionally focused on the individual, cognitive processes may manifest at many levels including the emergent group-level behavior that results from the interaction of multiple agents and their environment.
Roberts, M. E., & Goldstone, R. L. (2006). EPICURE: Spatial and Knowledge Limitations in Group Foraging. Adaptive Behavior, 14, 291-313.
We propose an agent-based model of group foraging, EPICURE, for patchily distributed resources. Each agent makes probabilistic movement decisions in a gridworld through a linear combination of current perceptual information and a reinforcement history. EPICURE captures the empirical results from several foraging conditions in Goldstone and Ashpole (2004) and Goldstone, Ashpole, and Roberts (2005), and it leads to a re-evaluation of findings from those papers. In particular, human foragers show contingent usage of information, initially using social information to discover resource pools before private sampling information has been established. We describe a series of simulations that test the sources of resource undermatching often found in group foraging experiments. After testing the effects of foragers’ starting locations, travel costs, the number of foragers, and the size of uniform food distributions, we discuss a novel hypothesis for undermatching. Spatial constraints lead to inadequate individual and group information sampling and cause group undermatching. The foraging group size, food rate, spatial distribution of food, and resulting forager reinforcement histories interact to produce undermatching, and occasionally overmatching, to resources.
Goldstone, R. L. (2006). The Complex systems see-change in education. The Journal of Learning Sciences, 15, 35-43.
The day when scientists have time to read broadly across chemistry, biology, physics and social sciences is long gone. Journals, conferences, and academic departmental structures are becoming increasingly specialized and myopic. As Peter Csermely (1999), one of the organizers of the International Forum of Young Scientists expresses it, “There is only a limited effort to achieve the appropriate balance between the discovery of new facts and finding their appropriate place and importance in the framework of science. Science is not self-integrating, and there are fewer and fewer people taking responsibility for ‘net-making” (p. 1621). One possible response to this fragmentation of science is to simply view it as inevitable. Horgan (1996) argues that the age of fundamental scientific theorizing and discoveries has passed, and that all that is left to be done is refining the details of theories already laid down by the likes of Einstein, Darwin, and Newton. Complex systems researchers, and learning scientists more generally, offer an alternative perspective, choosing to reverse the trend toward increasing specialization.
Goldstone, R. L., Jones, A., & Roberts, M. E. (2006). Group path formation. IEEE Transactions on System, Man, and Cybernetics, Part A, 36, 611-620.
When people make choices within a group, they are frequently influenced by the choices made by others. We have experimentally explored the general phenomenon of group behavior where an early action facilitates subsequent actions. Our concrete instantiation of this problem is group path formation where people travel between destinations with the travel cost for moving onto a location inversely related to the frequency with which others have visited the location. We compare the resulting paths to optimal solutions [Minimal Steiner Trees (MSTs)] and the “Active Walker” model of pedestrian motion from biophysics. There were systematic deviations from beeline pathways in the direction of MST. These deviations showed asymmetries (people took different paths from A to B than they did from B to A) and varied as a function of the topology of the destinations, the duration of travel, and the absolute scale of the world. The Active Walker model accounted for many of these results, in addition to correctly predicting the approximate spatial distribution of steps.
Goldstone, R. L., & Roberts, M. E. (2006). Self-organized trail systems in groups of humans. Complexity, 11, 43-50.
We have developed an experimental platform for studying the trail systems that spontaneously emerge when people are motivated to take advantage of the trails left by others. In this virtual environment, the participants’ task is to reach randomly selected destinations whileminimizing travel costs. The travel cost of every patch in the environment is inversely related to the number of times the patch was visited by others. The resulting trail systems are a compromise between people going to their destinations and going where many people have previously traveled. We compare the results from our group experiments to the Active Walker model of pedestrian motion from biophysics. The ActiveWalker model accounted for deviations of trails from the beeline paths, the gradual merging of trails over time, and the influences of scale and configuration of destinations on trail systems, as well as correctly predicting the approximate spatial distribution of people’s steps. Two deviations of the model from empirically obtained results were corrected by (1) incorporating a distance metric sensitive to canonical horizontal and vertical axes, and (2) increasing the influence of a trail’s travel cost on an agent’s route as the agent approaches its destination.
Goldstone, R. L., & Janssen, M. A. (2005). Computational models of collective behavior. Trends in Cognitive Science, 9, 424-430.
Computational models of human collective behavior offer promise in providing quantitative and empirically verifiable accounts of how individual decisions lead to the emergence of group-level organizations. Agent-based models (ABMs) describe interactions among individual agents and their environment, and provide a process-oriented alternative to descriptive mathematical models. Recent ABMs provide compelling accounts of group pattern formation, contagion, and cooperation, and can be used to predict, manipulate, and improve upon collective behavior. ABMs overcome an assumption underlying much of cognitive science – that the individual is the critical unit of cognition. The advocated alternative is that individuals participate in collective organizations that they may not understand or even perceive, and that these organizations affect and are affected by individual behavior.
Goldstone, R. L., Feng, Y., & Rogosky, B. (2005). Connecting concepts to the world and each other. In D. Pecher & R. Zwaan (Eds.) Grounding cognition: The role of perception and action in memory, language, and thinking. Cambridge: Cambridge University Press. (pp. 292-314)
How can well tell that two people both have a concept of dog, gold, or car despite differences in their conceptual knowledge? Two kinds of information can be used to translate between the concepts in two persons’ minds: the internal relations between concepts within each person’s mind, and external grounding of the concepts. We present a neural network model called ABSURDIST (Aligning Between Systems Using Relations Derived Inside Systems Themselves) that integrates internal and external determinants of conceptual meaning to find translations across people or other systems. The model shows that appropriate translations can be found by considering only similarity relations among concepts within a person. However, simulations also indicate synergistic interactions between internal and external sources of information. ABSURDIST is then applied to analogical reasoning, dictionary translation, translating between web-based ontologies, subgraph matching, and object recognition. The performance of ABSURDIST suggests the utility of concepts that are simultaneously externally grounded and enmeshed within a conceptual system.
There has been a long history of research into the structure and evolution of mankind’s scientific endeavor. However, recent progress in applying the tools of science to understand science itself has been unprecedented because only recently has there been access to high-volume and high-quality data sets of scientific output (e.g., publications, patents, grants), as well as computers and algorithms capable of handling this enormous stream of data. This paper reviews major work on models that aim to capture and recreate the structure and dynamics of scientific evolution. We then introduce a general process model that simultaneously grows co-author and paper-citation networks. The statistical and dynamic properties of the networks generated by this model are validated against a 20-year data set of articles published in the Proceedings of the National Academy of Science. Systematic deviations from a power law distribution of citations to papers are well fit by a model that incorporates a partitioning of authors and papers into topics, a bias for authors to cite recent papers, and a tendency for authors to cite papers cited by papers that they have read. In this TARL model (for Topics, Aging, and Recursive Linking), the number of topics is linearly related to the clustering coefficient of the simulated paper citation network.
The external world must be filtered through our perceptual systems before it can have an impact upon us. That is, the world we experience is formed by our perceptual processing. However, it is not viciously circular to argue that our perceptual systems are reciprocally formed by our experiences. In fact, it is because our experiences are necessarily based on our perceptual systems that these perceptual systems must be shaped so that our experiences are appropriate and useful for dealing with our world.
In what follows, I will argue that the “building blocks” an observer uses for construing their world depends on the observer’s history, training, and acculturation. These factors, together with psychophysical constraints, mold one’s set of building blocks. Researchers who have proposed fixed sets of hard-wired primitives are exactly right in one sense — the combinatorics of objects, words, scenes, and scenarios strongly favor componential representations. However, this does not necessitate that the components be hard-wired. By developing new components to subserve particular tasks and environments, a newly important discrimination can generate building blocks that are tailored for the discrimination. Adaptive building blocks are likely to be efficient because they can be optimized for idiosyncratic needs and environments.
Goldstone, R. L., & Sakamoto, Y. (2003). The Transfer of Abstract Principles Governing Complex Adaptive Systems. Cognitive Psychology, 46, 414-466.
Four experiments explored participants’ understanding of the abstract principles governing computer simulations of complex adaptive systems. Experiment 1 revealed better transfer between computer simulations when they were governed by the same abstract principle, even when the simulations’ domains were dissimilar. Experiments 2 and 3 showed better transfer of abstract principles across simulations that were relatively dissimilar, and that this effect was due to participants who performed relatively poorly on the initial simulation. In Experiment 4, participants showed better abstract understanding of a simulation when it was depicted with concrete rather than idealized graphical elements. However, for poor performers, the idealized version of the simulation transferred better to a new simulation governed by the same abstraction. The results are interpreted in terms of competition between abstract and concrete construals of the simulations. Individuals prone toward concrete construals tend to overlook abstractions when concrete properties or superficial similarities are salient.
Goldstone, R. L., & Rogosky, B. J. (2002). Using relations within conceptual systems to translate across conceptual systems, Cognition, 84, 295-320.
We explore one aspect of meaning, the identification of matching concepts across systems (e.g. people, theories, or cultures). We present a computational algorithm called ABSURDIST (Aligning Between Systems Using Relations Derived Inside Systems for Translation) that uses only within-system similarity relations to find between-system translations. While illustrating the sufficiency of within-system relations to account for translating between systems, simulations of ABSURDIST also indicate synergistic interactions between intrinsic, within-system information and extrinsic information.
Here is a brief description and commentary on ABSURDIST:
Dietrich, E. (2003). An ABSURDIST model vindicates a venerable theory. Trends in Cognitive Science, 7, 57-59.
Goldstone, R. L., & Rogosky, B. J. (2002). The role of roles in translating across conceptual systems, Proceedings of the Twenty-fourth Annual Conference of the Cognitive Science Society. Hillsdale, New Jersey: Lawrence Erlbaum Associates. (pp. 369-374).
According to an “external grounding” theory of meaning, a concept’s meaning depends on its connection to the external world. By a “conceptual web” account, a concept’s meaning depends on its relations to other concepts within the same system. We explore one aspect of meaning, the identification of matching concepts across systems (e.g. people, theories, or cultures). We present a computational algorithm called ABSURDIST (Aligning Between Systems Using Relations Derived Inside Systems for Translation) that uses only within-system similarity relations to find between-system translations. While illustrating the sufficiency of a conceptual web account for translating between systems, simulations of ABSURDIST also indicate powerful synergistic interactions between intrinsic, within-system information and extrinsic information. Applications of the algorithm to issues in object recognition, shape analysis, automatic translation, human analogy and comparison making, pattern matching, neural network interpretation, and statistical analysis are described.
Goldstone, R. L. (1998). Hanging Together: A connectionist model of similarity. In J. Grainger & A. M. Jacobs (Eds.) Localist Connectionist Approaches to Human Cognition. (pp. 283 – 325). Mahwah, NJ: Lawrence Erlbaum Associates.
Human judgments of similarity have traditionally been modelled by measuring the distance between the compared items in a psychological space, or the overlap between the items` featural representations. An alternative approach, inspired jointly by work in analogical reasoning (D. Gentner, 1983; K. T. Holyoak & P. Thagard, 1989) and interactive activation models of perception (J. L. McClelland & D. E. Rumelhart, 1981), views the process of judging similarity as one of establishing alignments between the parts of compared entities. A localist connectionist model of similarity, SIAM, is described wherein units represent correspondences between scene parts, and these units mutually and concurrently influence each other according to their compatability. The model is primarily applied to similarity rating tasks, but is also applied to other indirect measures of similarity, to judgments of alignment between scene parts, to impressions of comparison difficulty, and to patterns of perceptual sensitivity for matching and mismatching features.
A continuum between purely isolated and purely interrelated concepts is described. A concept is interrelated to the extent that it is influenced by other concepts. Methods for manipulating and identiying a concept`s degree of interrelatedness are introduced. Relatively isolated concepts are empirically identified by a relatively large use of nondiagnostic features, and by better categorization performance for a concept`s prototype than for a caricature of the concept. Relatively interrelated concepts are identified by minimal use of nondiagnostic features, and by better categorization performance for a caricature than a prototype. A concept is likely to be relatively isolated when: subjects are instructed to create images for their concepts rather than find discriminating features, concepts are given unrelated labels, and the categories that are displayed alternate rarely between trials. The entire set of manipulations and measurements supports a graded distinction between isolated and interrelated concepts. The distinction is applied to current models of category learning, and a connectionist framework for interpreting the empirical results is presented.
The question of “what makes things seem similar?” is important both for the pivotal role of similarity in theories of cognition and for an intrinsic interest in how people make comparisons. Similarity frequently involves more than listing the features of the things to be compared and comparing the lists for overlap. Often, the parts of one thing must be aligned or placed in correspondence with the parts of the other. The quantitative model with the best overall fit to human data assumes an interactive activation process whereby correspondences between the parts of compared things mutually and concurrently influence each other. An essential aspect of this model is that matching and mismatching features influence similarity more if they belong to parts that are placed in correspondence. In turn, parts are placed in correspondence if they have many features in common and if they are consistent with other developing correspondences.