Jun 21, 2023 · In this paper, we address this challenge, by developing an algorithm -- OPAX -- for active exploration. OPAX uses well-calibrated probabilistic ...
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The paper presents an active exploration method (OPAX) for dynamics model learning. The method seeks to maximize information gain, while being optimistic about ...
In this paper, we address this challenge, by developing an algorithm – OPAX– for active exploration. OPAX uses well-calibrated probabilistic models to quantify ...
May 30, 2024 · In this paper, we address this challenge, by developing an algorithm - OPAX- for active exploration. OPAX uses well-calibrated probabilistic models.
Oct 30, 2023 · Contributions In this paper, we introduce a new algorithm, Optimistic Active eXploration (OPAX), designed to actively learn nonlinear dynamics ...
View recent discussion. Abstract: Reinforcement learning algorithms commonly seek to optimize policies for solving one particular task.
In this paper, we address this challenge, by developing an algorithm -- OPAX -- for active exploration. OPAX uses well-calibrated probabilistic models to ...
Optimistic Active Exploration of Dynamical Systems. Implementation Model-based RL algorithms with basic optimizer. Currently implemented: SAC; CEM optimizer ...
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End-to-end pixel-based deep active inference for body perception and action ... Optimistic active exploration of dynamical systems. L Treven, C Sancaktar, S ...
MaxInfoRL - Boosting exploration in reinforcement learning through information gain maximization ... Optimistic Active Exploration of Dynamical Systems. project ...