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Planning, the process of evaluating the future consequences of actions, is typically formalized as search over a decision tree. This procedure increases expected rewards but is computationally expensive. Past attempts to understand how people mitigate the costs of planning have been guided by heuristics or the accumulation of prior experience, both of which are intractable in novel, high-complexity tasks. In this work, we propose a normative framework for optimizing the depth of tree search. Specifically, we model a metacognitive process via Bayesian inference to compute optimal planning depth. We show that our model makes sensible predictions over a range of parameters without relying on retrospection and that integrating past experiences into our model produces results that are consistent with the transition from goal-directed to habitual behavior over time and the uncertainty associated with prospective and retrospective estimates. Finally, we derive an online variant of our model that replicates these results.

CogSci 2021

Planning to plan: a Bayesian model for optimizing the depth of decision tree search

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**Dear Colleagues,**

Welcome to the 43rd Annual Conference of the Cognitive Science Society! 

This year’s conference brings together the latest research from all Cognitive Science and also highlights this year’s theme **Comparative Cognition: Animal Minds.** 

The program features four plenary speakers: Friederike Range (University of Veterinary Medicine, Vienna), Onur Güntürkün (Ruhr University Bochum), Julia Fischer (University of Göttingen), and Erich Jarvis (The Rockefeller University). The keynotes and invited symposia showcase the broad spectrum of ideas that encompass the conference theme of comparative cognition. 

Further, the program includes the Rumelhart Prize keynote presentation by Susan Goldin-Meadow (University of Chicago), and symposia to celebrate the winner of the Elman Prize: Wei Ji Ma (New York University), the Heineken Award winner Robert Zatorre (McGill University), and the Robert J. Glushko Dissertation Prizes session.

The program committee for CogSci 2021 received 1,025 submissions, including 710 full papers, 275 member abstracts, 8 publication-based talks, as well as 15 proposals for symposia, and 17 for workshops and tutorials. After a rigorous review process, the committee selected 152 papers for oral presentation and inclusion in the conference proceedings (14.8%), 332 papers for poster presentation and inclusion in the proceedings (32.4%), and 175 papers for poster presentation with inclusion of abstracts in the proceedings (17.1%) We also selected 275 submitted member abstracts. In addition, we accepted 6 publication-based talks, 12 symposia, and 9 workshops and tutorials to make for an exciting and inclusive program.

We hope that you enjoy the conference this year!<br><br>

**Your Program Chairs,**
![](https://assets.underline.io/uploads/markdown_image/1/image/99984908caba5e6453e5fc5ba34f3507.jpg)

**Learn more about the Vienna Cognitive Science Hub at the University of Vienna, hosts of CogSci 2021**

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To review the proceedings for the conference or review the searchable program, please visit the [website](https://cognitivesciencesociety.org/program/).


The Cognitive Science Society brings together researchers from around the world who hold a common goal: understanding the nature of the human mind. The mission of the Society is to promote Cognitive Science as a discipline, and to foster scientific interchange among researchers in various areas of study, including Artificial Intelligence, Linguistics, Anthropology, Psychology, Neuroscience, Philosophy, and Education. The Society is a non-profit professional organization and its activities include sponsoring an annual conference and publishing the journals Cognitive Science and TopiCS.

technical paper

Many real-world tasks require agents to coordinate their behavior to achieve shared goals. Successful collaboration requires not only adopting the same communicative conventions, but also grounding these conventions in the same task-appropriate conceptual abstractions. We investigate how humans use natural language to collaboratively solve physical assembly problems more effectively over time. Human participants were paired up in an online environment to reconstruct scenes containing two block towers. One participant could see the target towers, and sent assembly instructions for the other participant to reconstruct. Participants provided increasingly concise instructions across repeated attempts on each pair of towers, using more abstract referring expressions that captured each scene's hierarchical structure. To explain these findings, we extend recent probabilistic models of ad hoc convention formation with an explicit perceptual learning mechanism. These results shed light on the inductive biases that enable intelligent agents to coordinate upon shared procedural abstractions.

Learning to communicate about shared procedural abstractions

Adaptive decisions require that decision makers factor in the subjective values of different possible outcomes, and the probability of these outcomes occurring. Subjective values depend, among other things, on how far an outcome is away in time. This can be captured by assessing an individual’s delay discounting of different options. An individual’s risk preference also affects how attractive particular choice options appear to them. In humans, probability discounting and delay discounting are often related. People who show more risky behaviors also tend to be more impulsive and less patient. Based on such findings, single-process models of delay discounting and probability discounting have been suggested. In the current study, we tested if this relationship is equally present in chimpanzees, one of human’s closest extant evolutionary relatives. We presented 23 chimpanzees with a patience task and a risky-choice task. The patience task was designed to explicitly distinguish between delay preference and self-control (i.e., the ability to wait a given delay). Still, we found no strong correlations between risk and delay preferences. As this task has not been used with humans before, we implemented a computerized version and tested it in a sample of twenty adult participants. Initial results indicate that the task is well suited to capture patience, and it makes a promising candidate to be used in behavioral delay discounting experiments in humans.

Relationship between Delay Discounting and Risk Preference in Chimpanzees (Pan troglodytes) and Humans

Cooperation experiments have long been used to explore the cognition underlying animals' coordination towards a shared goal. While the ability to understand the need for a partner has been demonstrated in a number of species, far fewer studies have explored the behavioral strategies animals use to coordinate their behavior in such tasks. Here, we investigate the strategies two dolphin dyads used to coordinate their behavior during a cooperative button-pressing task that required precise behavioral synchronization. Both dyads were more likely to succeed if they used whistles prior to pressing their buttons, but the results showed that they adopted different strategies. Specifically, one dyad favored physical synchrony, waiting nearby for their partner and swimming together to approach the buttons. The other dyad was much more vocal, and more likely to swim independently before coordinating at the buttons. Only for this second dyad did increased whistling lead to more success. Our results suggest that bottlenose dolphins have the behavioral flexibility to employ either vocal signals or physical synchrony to coordinate their cooperative efforts.

In Sync or Vocal? How Bottlenose Dolphins Coordinate in a Cooperative Task

Attention can be biased by the previous learning and experience. We present an algorithmic-level model of this bias in visual attention that predicts quantitatively how bottom-up, top-down and selection history compete to control attention. In the model, the output of saliency maps as bottom-up guidance interacts with a history map that encodes learning effects and a top-down task control to prioritize visual features. We test the model on a reaction-time (RT) data set from the experiment presented by Feldmann-Wüstefeld et al. 2015. The model accurately predicts parameters of reaction time distributions from an integrated priority map that is comprised of an optimal, weighted combination of separate maps. Analysis of the weights confirms learning history effects on attention guidance.

A model of selection history in visual attention

Primate cognition research allows us to reconstruct the evolution of human cognition. However, temporal and contextual factors that induce variation in cognitive studies with great apes are poorly understood. Here we report on a longitudinal study where we repeatedly tested a comparatively large sample of great apes (N = 40) with the same set of cognitive measures. We investigated the stability of group-level results, the reliability of individual differences, and the relation between cognitive performance and individual-level characteristics. We found results to be relatively stable on a group level. Some, but not all, tasks showed acceptable levels of reliability. Cognitive performance across tasks was not systematically related to any particular individual-level predictor. This study highlights the importance of methodological considerations – especially when studying individual differences – on the route to building a more robust science of primate cognitive evolution.

A Longitudinal Study of Great Ape Cognition: Stability, Reliability and the Influence of Individual Characteristics

People can produce drawings of specific entities (e.g., Garfield), as well as general categories (e.g., ``cat''). What explains this ability to produce such varied drawings of even highly familiar object concepts? We hypothesized that drawing objects at different levels of abstraction depends on both sensory information and representational goals, such that drawings intended to portray a recently seen object preserve more detail than those intended to represent a category. Participants drew objects cued either with a photo or a category label. For each cue type, half the participants aimed to draw a specific exemplar; the other half aimed to draw the category. We found that label-cued category drawings were the most recognizable at the basic level, whereas photo-cued exemplar drawings were the least recognizable. Together, these findings highlight the importance of task context for explaining how people use drawings to communicate visual concepts in different ways.

Visual communication of object concepts at different levels of abstraction

There have been recently multiple calls to investigate the rhythmic behaviors (RBs) of nonhuman animals, as a way to gain insight into the evolution of human rhythm cognition and musicality. Currently, the empirical data from non-human species is scarce. Most strikingly, we lack data from chimpanzees (Pan troglodytes), our closest genetic relatives. Here, we present an observational study conducted at three sites (N=41), in which we systematically documented RBs in chimpanzees, with a particular focus on functional contexts, sex differences and emotional correlates. We found that RBs were frequent in chimpanzees, occurred primarily in social contexts, and often had social consequences. RBs were not exclusively associated with high arousal or playfulness. RBs were more frequent in males than females, but sex did not affect their social efficacy. Our findings are consistent with social theories on the evolution of musicality, but also highlight a role for RBs in chimpanzee inter-sexual communication.

Rhythmic behaviors in chimpanzees: range, functional contexts, sex differences and emotional correlates

Can people interpret communicative action modulations in terms of the actor’s distal goal? We investigated situations in which the proximal goal of an action (i.e., the movement endpoint) does not overlap with its distal goal (i.e., a final location beyond the movement endpoint). Participants were presented with animations of an object being moved at different velocities towards a designated endpoint. The distal goal, however, was for the object to be moved past this endpoint, to one of two occluded final locations. Participants were asked to select the location which they considered the likely distal goal of the action. As predicted, participants detected differences in movement velocity and, based on these differences, systematically mapped the movements to the two distal goal locations. These findings extend previous research on sensorimotor communication by demonstrating that communicative action modulations are not restricted to proximal goals but can also contain information about distal goals.

Understanding distal goals from proximal communicative actions

Paying attention to weight is important when deciding upon an object’s efficacy or value in various contexts (e.g. tool use, foraging). Proprioceptive discrimination learning, with objects that differ only in weight, has so far been investigated in a handful of primate species. Here we show that while Goffin’s cockatoos learn faster when additional colour cues are used, they can also quickly learn to discriminate between objects on the basis of their weight alone. Ultimately, the birds learned to discriminate between visually identical objects on the basis of weight much faster than primates, although methodological differences between tasks should be considered.

Goffin's cockatoos learn to discriminate objects based on weight alone in an object choice task

Speakers communicate to influence their partner's beliefs and shape their actions. Belief- and action-based objectives have been explored independently in recent computational models, but it has been challenging to explicitly compare or integrate them. Indeed, we find that they are conflated in standard referential communication tasks. To distinguish these accounts, we introduce a new paradigm called signaling bandits, generalizing classic Lewis signaling games to a multi-armed bandit setting where all targets in the context have some relative value. We develop three speaker models: a belief-oriented speaker with a purely informative objective; an action-oriented speaker with an instrumental objective; and a combined speaker which integrates the two by inducing listener beliefs that generally lead to desirable actions. We then present a series of simulations demonstrating that grounding production choices in future listener actions results in relevance effects and flexible uses of nonliteral language. More broadly, our findings suggest that language games based on richer decision problems are a promising avenue for insight into rational communication.

Planning to plan: a Bayesian model for optimizing the depth of decision tree search

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Learning to communicate about shared procedural abstractions

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Planning to plan: a Bayesian model for optimizing the depth of decision tree search

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Next from CogSci 2021

Learning to communicate about shared procedural abstractions

Similar lecture

The Role of Verbal and Visuospatial Working Memory in Supporting Mathematics Learning With and Without Hand Gesture

Stay up to date with the latest Underline news!

PRESENTATIONS

CONFERENCES

COMPANY

RESOURCES

Downloads