Oct 25, 2021 · In this work, we investigate a way of augmenting model-based RL, by additionally encouraging a learned model and value function to be jointly \ ...
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In this work, we investigate a way of augmenting model-based RL, by additionally encouraging a learned model and value function to be jointly self-consistent.
This paper brings Dreamer-style agent training to the MuZero architecture, and also proposes a self-consistency constraint that takes cues from Dyna, with a ...
Jun 10, 2024 · Learned models of the environment provide reinforcement learning (RL) agents with flexible ways of making predictions about the environment.
Nov 9, 2021 · The paper offers a new approach to model-based reinforcement learning with their idea of self-consistency of models and values. In the ...
Oct 25, 2021 · Learned models of the environment provide reinforcement learning (RL) agents with flexible ways of making predictions about the environment.
[PDF] Self-Consistent Models and Values - Semantic Scholar
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Oct 25, 2021 · This work investigates a way of augmenting model-based RL, by additionally encouraging a learned model and value function to be jointly ...
Self-consistency is a concept closely linked with mean-field theories. In mean-field treatment of the Schrodinger equation, interacting particles give off a ...
Mar 21, 2022 · Self-consistency leverages the intuition that a complex reasoning problem typically admits multiple different ways of thinking leading to its ...
Abstract. The term “self-consistency” was introduced in 1989 by Hastie and Stuetzle to describe the property that each point on a smooth curve.