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14 results

  • Chapter 8 - Representational Exchange in Human Social Learning

  • from Part II - How Do Humans Search for Information?
  • Edited by Irene Cogliati Dezza, University College London, Eric Schulz, Max-Planck-Institut für biologische Kybernetik, Tübingen, Charley M. Wu, Eberhard-Karls-Universität Tübingen, Germany
  • Book:
    The Drive for Knowledge
    Published online:
    19 May 2022
    Print publication:
    02 June 2022, pp 169-192

  • Summary

    What makes human social learning so powerful? While past accounts have sometimes prioritized finding the single capacity that makes the largest difference, our social learning abilities span a wide spectrum of capacities from the high-fidelity imitation of behaviors to inferring and learning from hidden mental states. Here, we propose that the power of human social learning lies not within a single capacity, but in our ability to flexibly arbitrate between different computations and to integrate their outputs. In particular, learners can directly copy the demonstrator’s actions in the absence of causal insight (policy imitation), infer their instrumental values (value inference), or infer their model of the world and intrinsic rewards (belief inference and reward inference). Each of these strategies trades off the cost of computation against the flexibility and compositionality of its outputs. Crucially, we have the capacity to arbitrate and exchange information between these representational formats. Human social learning, we suggest, is powerful not just because of the way it moves information between minds, but also because of the way it flexibly moves information within them.

  • Future Challenges

  • from Part III - Which Machinery Supports the Drive for Knowledge?
  • Edited by Irene Cogliati Dezza, University College London, Eric Schulz, Max-Planck-Institut für biologische Kybernetik, Tübingen, Charley M. Wu, Eberhard-Karls-Universität Tübingen, Germany
  • Book:
    The Drive for Knowledge
    Published online:
    19 May 2022
    Print publication:
    02 June 2022, pp 279-290

  • Summary

    This book has covered a wide range of new and exciting research in the science of information-seeking. Yet many open questions still remain. For example, how is information-seeking related to reward-seeking? What are the principles that enable us to acquire useful information with computational efficiency, despite possessing limited cognitive capacities and knowledge? Which aspects of our neural machinery are unique to information-seeking, and what is shared across other cognitive systems? How does the science of information-seeking inform important societal issues, such as fake news, conspiracy theories, and education?

The Drive for Knowledge
  • The Science of Human Information Seeking
  • Edited by Irene Cogliati Dezza, Eric Schulz, Charley M. Wu
  • Published online:
    19 May 2022
    Print publication:
    02 June 2022
  • Humans constantly search for and use information to solve a wide range of problems related to survival, social interactions, and learning. While it is clear that curiosity and the drive for knowledge occupies a central role in defining what being human means to ourselves, where does this desire to know the unknown come from? What is its purpose? And how does it operate? These are some of the core questions this book seeks to answer by showcasing new and exciting research on human information-seeking. The volume brings together perspectives from leading researchers at the cutting edge of the cognitive sciences, working on human brains and behavior within psychology, computer science, and neuroscience. These vital connections between disciplines will continue to lead to further breakthroughs in our understanding of human cognition.