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Bounded Rationality, Abstraction, and Hierarchical Decision-Making: An Information-Theoretic Optimality Principle.

, , , and . Front. Robotics and AI, (2015)

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A Unified Bellman Optimality Principle Combining Reward Maximization and Empowerment., , and . NeurIPS, page 7867-7878. (2019)Shaking the foundations: delusions in sequence models for interaction and control., , , , , , , , , and 9 other author(s). CoRR, (2021)Noise-induced up/Down Dynamics in Scale-Free neuronal Networks., , and . Int. J. Bifurc. Chaos, (2012)Neural Networks and the Chomsky Hierarchy, , , , , , , , , and 1 other author(s). The Eleventh International Conference on Learning Representations, (2023)A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function., , , , and . NIPS, page 3014-3022. (2012)Learning Universal Predictors., , , , , , , , , and 1 other author(s). ICML, OpenReview.net, (2024)Beyond Bayes-optimality: meta-learning what you know you don't know., , , , , , , , , and 4 other author(s). CoRR, (2022)Neural Networks and the Chomsky Hierarchy., , , , , , , , and . CoRR, (2022)Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning., and . CoRL, volume 100 of Proceedings of Machine Learning Research, page 360-373. PMLR, (2019)Memory-Based Meta-Learning on Non-Stationary Distributions., , , , , , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 11173-11195. PMLR, (2023)