How to Grow a Mind: Statistics, Structure, and Abstraction
Science, 2011. [All Versions]. [Preprint]. This review describes recent approaches to reverse-engineering human learning and cognitive development and, in parallel, engineering more humanlike machine learning systems. Computational models that perform probabilistic inference…
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Building Machines That Learn and Think Like People cambridge.org
Behavioral and Brain Sciences, 2017. [All Versions]. [Preprint]. Recent progress in artificial intelligence has renewed interest in building systems that learn and think like people. Many advances have come from using deep neural networks trained end-to-end in tasks such as…
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Theory of Minds: Understanding Behavior in Groups through Inverse Planning aaai.org
AAAI'19, 2019. [All Versions]. Towards the goal of building machine-learning algorithms with human-like social intelligence, this paper develops a generative model of multiagent action understanding based on a novel representation for these latent relationships called…
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Deep Learning: How the Mind Overrides Experience hk1lib.org
Cambridge University Press, 2011. [All Versions].
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Cognitive Science as a Source of Forward and Inverse Models of Human Decisions for Robotics and Control cocosci.princeton.edu
Annual Review of Control, Robotics, and Autonomous Systems, 2022. [All Versions]. The review focuses on how cognitive science can provide forward models of human decision-making and inverse models of how humans think about others’ decision-making. The authors highlight relevant…
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Do People Ask Good Questions? link.springer.com
Computational Brain & Behavior, 2018. [All Versions].
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Probabilistic models of cognition: Conceptual foundations cell.com
Trends in Cognitive Sciences, 2006. [All Versions]. Remarkable progress in the mathematics and computer science of probability has led to a revolution in the scope of probabilistic models. In particular, ‘sophisticated’ probabilistic methods apply to structured relational…
AGI & CoCoSci › Papers > Bayesian Modeling > Bayesian Induction: “Science, 2011. [All Versions]. [Preprint]. This review describes recent approaches to reverse-engineering human learning and cognitive development and, in parallel, engineering more humanlike machine learning systems. Computational models that perform probabilistic inference…”