Perception and simulation during concept learning

Weitnauer, E., Goldstone, R. L., & Ritter, H. (in press). Perception and simulation during concept learning.  Psychological Review.

A key component of humans’ striking creativity in solving problems is our ability to construct novel descriptions to help us characterize novel concepts. Bongard problems, which challenge the problem solver to come up with a rule for distinguishing visual scenes that fall into two categories, provide an elegant test of this ability. Bongard problems are challenging for both human and machine category learners because only a handful of example scenes are presented for each category, and they often require the open-ended creation of new descriptions. A new type of Bongard problem called Physical Bongard Problems (PBPs) is introduced, which requires solvers to perceive and predict the physical spatial dynamics implicit in the depicted scenes. The PATHS (Perceiving And Testing Hypotheses on Structures) computational model which can solve many PBPs is presented, and compared to human performance on the same problems. PATHS and humans are similarly affected by the ordering of scenes within a PBP. Spatially or temporally juxtaposing similar (relative to dissimilar) scenes promotes category learning when the scenes belong to different categories, but hinders learning when the similar scenes belong to the same category. The core theoretical commitments of PATHS, which we believe to also exemplify open-ended human category learning, are a) the continual perception of new scene descriptions over the course of category learning, b) the context-dependent nature of that perceptual process, in which the perceived scenes establish the context for the perception of subsequent scenes, c) hypothesis construction by combining descriptions into explicit rules, and d) bi-directional interactions between perceiving new aspects of scenes and constructing hypotheses for the rule that distinguishes categories.

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Carving joints into nature: reengineering scientific concepts in light of concept-laden evidence

Dubova, M., & Goldstone, R. L. (2023). Carving joints into nature: reengineering scientific concepts in light of concept-laden evidence.  Trends in Cognitive Sciences, 27: 7, 656-670.

A new wave of proposals suggests that scientists must reassess scientific concepts in light of accumulated evidence. However, reengineering scientific concepts in light of data is challenging because scientific concepts affect the evidence itself in multiple ways. Among other possible influences, concepts (i) prime scientists to overemphasize within-concept similarities and betweenconcept differences; (ii) lead scientists to measure conceptually relevant dimensions more accurately; (iii) serve as units of scientific experimentation, communication, and theory-building; and (iv) affect the phenomena themselves. When looking for improved ways to carve nature at its joints, scholars must take the concept-laden nature of evidence into account to avoid entering a vicious circle of concept-evidence mutual substantiation.

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Cognitive Science of Augmented Intelligence

Dubova, M., Galesic, M., & Goldstone, R. L. (2022).  Cognitive Science of Augmented Intelligence.  Cognitive Science, 46, 1-6, e13229.

Cognitive science has been traditionally organized around the individual as the basic unit of cognition. Despite developments in areas such as communication, human-machine interaction, group behavior, and community organization, individual-centric approach heavily dominates both cognitive research and its application. A promising direction for cognitive science is the study of augmented intelligence, or the way social and technological systems interact with and extend individual cognition. The cognitive science of augmented intelligence holds promise in helping society tackle major real-world challenges that can only be discovered and solved by teams made of individuals and machines with complementary skills who can productively collaborate with each other.

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Partial copying and the role of diversity in social learning performance

Campbell, C., Izquierdo, E. & Goldstone, R. L. (2022).  Partial copying and the role of diversity in social learning performance. Collective Intelligence, 1:1, 1-15. 10.1177/26339137221081849

One major way that people engage in adaptive problem solving is by imitating others’ solutions. Prominent simulation models have found imperfect imitation advantageous, but the interactions between copying amount and other prevalent aspects of social learning strategies have been underexplored. Here, we explore the consequences for a group when its members engage in strategies with different degrees of copying, solving search problems of varying complexity, in different network topologies that affect the solutions visible to each member. Using a computational model of collective problem solving, we demonstrate that the advantage of partial copying is robust across these conditions, arising from its ability to maintain diversity. Partial copying delays convergence generally but especially in globally connected networks, which are typically associated with diversity loss, allowing more exploration of a problem space.We show that a moderate amount of diversity maintenance is optimal and strategies can be adjusted to find that sweet spot.

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Reinforcement communication learning in different social network structures

Dubova, M., Moskvichev, A., & Goldstone, R. L. (2020). Reinforcement Communication Learning in Different Social Network Structures. International Conference on Machine Learning, 1st Language and Reinforcement Learning Workshop. 

Social network structure is one of the key determinants of human language evolution. Previous work has shown that the network of social interactions shapes decentralized learning in human groups, leading to the emergence of different kinds of communicative conventions. We examined the effects of social network organization on the properties of communication systems emerging in decentralized, multi-agent reinforcement learning communities. We found that the global connectivity of a social network drives the convergence of populations on shared and symmetric communication systems, preventing the agents from forming many local ‚Äúdialects‚ÄĚ. Moreover, the agent‚Äôs degree is inversely related to the consistency of its use of communicative conventions. These results show the importance of the basic properties of social network structure on reinforcement communication learning and suggest a new interpretation of findings on human convergence on word conventions.

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A three-site reproduction of the Joint Simon Effect with the NAO robot

Strait, M., Lier, F., Bernotat, J., Wachsmuth, S., Eyssel, F., Goldstone, R. L., & Sabanovic, S. (2020).  A three-site reproduction of the Joint Simon Effect with the NAO robot.  15th Annual International Conference on Human Robot Interaction.  Cambridge, England.  Association for Computing Machinery (ACM) & Institute of Electrical and Electronics Engineers (IEEE).  (pp. 103-111).  New York: ACM.

The generalizability of empirical research depends on the reproduction of findings across settings and populations. Consequently, generalizations demand resources beyond that which is typically available to any one laboratory. With collective interest in the joint Simon effect (JSE) ‚Äď a phenomenon that suggests people work more effectively with humanlike (as opposed to mechanomorphic) robots ‚Äď we pursued a multi-institutional research cooperation between robotics researchers, social scientists, and software engineers. To evaluate the robustness of the JSE in dyadic human-robot interactions, we constructed an experimental infrastructure for exact, lab-independent reproduction of robot behavior. Deployment of our infrastructure across three institutions with distinct research orientations (well-resourced versus resource-constrained) provides initial demonstration of the success of our approach and the degree to which it can alleviate technical barriers to HRI reproducibility. Moreover, with the three deployments situated in culturally distinct contexts (Germany, the U.S. Midwest, and the Mexico-U.S. Border), observation of a JSE at each site provides evidence its generalizability across settings and populations.

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Quantifying Emergent, Dynamic Tonal Coordination in Collaborative Musical Improvisation

Setzler, M., & Goldstone, R. L. (2020).  Quantifying Emergent, Dynamic Tonal Coordination in Collaborative Musical Improvisation.  Proceedings of the 42nd Annual Conference of the Cognitive Science Society. (pp. 461-466).  Toronto, CA. Cognitive Science Society.

Groups of interacting individuals often coordinate in service of abstract goals, such as the alignment of mental representations in conversation, or the generation of new ideas in group brainstorming sessions. What are the mechanisms and dynamics of abstract coordination? This study examines coordination in a sophisticated paragon domain: collaboratively improvising jazz musicians. Remarkably, freely improvising jazz ensembles collectively produce coherent tonal structure (i.e. melody and harmony) in real time performance without previously established harmonic forms. We investigate how tonal structure emerges out of interacting musicians, and how this structure is constrained by underlying patterns of coordination. Dyads of professional jazz pianists were recorded improvising in two conditions of interaction: a ‚Äėcoupled‚Äô condition in which they could mutually adapt to one another, and an ‚Äėoverdubbed‚Äô condition which precluded mutual adaptation. Using a computational model of musical tonality, we show that this manipulation effected the directed flow of tonal information amongst pianists, who could mutually adapt to one another‚Äôs notes in coupled trials, but not in overdubbed trials. Consequently, musicians were better able to harmonize with one another in coupled trials, and this ability increased throughout the course of improvised performance. We present these results and discuss their implications for music technology and joint action research more generally.

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How much to copy from others?

Campbell, C., Izquierdo, E. & Goldstone, R. L. (2020).  How much to copy from others? The role of partial copying in social learning.  Proceedings of the 42nd Annual Conference of the Cognitive Science Society. (pp. 916-922). Toronto, Canada: Cognitive Science Society.

One of the major ways that people engage in adaptive problem solving is by copying the solutions of others. Most of the work on this field has focused on three questions: when to copy, who to copy from, and what to copy. However, how much to copy has been relatively less explored. In the current research, we are interested in the consequences for a group when its members engage in social learning strategies with different tendencies to copy entire or partial solutions and different complexities of search problems. We also consider different network topologies that affect the solutions visible to each member. Using a computational model of collective problem solving, we demonstrate that strategies where social learning involves partial copying outperform strategies where individuals copy entire solutions. We analyze the exploration/exploitation dynamics of these social learning strategies under the different conditions.

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Reconstructing Maps from Text

Avery, J. E., Goldstone, R. L., & Jones, M. N. (2020).  Reconstructing Maps from Text.  Proceedings of the 42nd Annual Conference of the Cognitive Science Society. (pp. 557-563).  Toronto, CA. Cognitive Science Society.

 Previous research has demonstrated that Distributional Semantic Models (DSMs) are capable of reconstructing maps from news corpora (Louwerse & Zwaan, 2009) and novels (Louwerse & Benesh, 2012). The capacity for reproducing maps is surprising since DSMs notoriously lack perceptual grounding (De Vega et al., 2012). In this paper we investigate the statistical sources required in language to infer maps, and resulting constraints placed on mechanisms of semantic representation. Study 1 brings word co-occurrence under experimental control to demonstrate that direct co-occurrence in language is necessary for traditional DSMs to successfully reproduce maps. Study 2 presents an instance-based DSM that is capable of reconstructing maps independent of the frequency of co-occurrence of city names. 

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Becoming cognitive science

Goldstone, R. L. (2019).  Becoming cognitive science.  Topics in Cognitive Science, 1-12.

Cognitive science continues to make a compelling case for having a coherent, unique, and fundamental¬†subject of inquiry: What is the nature of minds, where do they come from, and how do¬†they work? Central to this inquiry is the notion of agents that have goals, one of which is their¬†own persistence, who use dynamically constructed knowledge to act in the world to achieve those¬†goals. An agentive perspective explains why a special class of systems have a cluster of co-occurring¬†capacities that enable them to exhibit adaptive behavior in a complex environment: perception,¬†attention, memory, representation, planning, and communication. As an intellectual endeavor,¬†cognitive science may not have achieved a hard core of uncontested assumptions that Lakatos¬†(1978) identifies as emblematic of a successful research program, but there are alternative conceptions¬†according to which cognitive science has been successful. First, challenges of the early, core¬†tenet of ‚ÄúMind as Computation‚ÄĚ have helped put cognitive science on a stronger foundation‚ÄĒone¬†that incorporates relations between minds and their environments. Second, even if a full cross-disciplinary¬†theoretic consensus is elusive, cognitive science can inspire distant, deep, and transformative¬†connections between pairs of fields. To be intellectually vital, cognitive science need not¬†resemble a traditional discipline with its associated insularity and unchallenged assumptions.¬†Instead, there is strength and resilience in the diverse perspectives and methods that cognitive¬†science assembles together. This interdisciplinary enterprise is fragile and perhaps inherently¬†unstable, as the looming absorption of cognitive science into psychology shows. Still, for many¬†researchers, the excitement and benefits of triangulating on the nature of minds by integrating¬†diverse cases cannot be secured by a stable discipline with an uncontested core of assumptions.

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