Predictive Representations: Building Blocks of Intelligence
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Updated: Jun 14, 2025

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Published on: September 11, 2021
Wilka Carvalho1, Momchil S Tomov2,3, William de Cothi4
1Kempner Institute for the Study of Natural and Artificial Intelligence, Harvard University, Cambridge, MA 02134, U.S.A. wcarvalho92@gmail.com.
Abstract:
Adaptive behavior often requires predicting future events. The theory of reinforcement learning prescribes what kinds of predictive representations are useful and how to compute them. This review integrates these theoretical ideas with work on cognition and neuroscience. We pay special attention to the successor representation and its generalizations, which have been widely applied as both engineering tools and models of brain function. This convergence suggests that particular kinds of predictive representations may function as versatile building blocks of intelligence.
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