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Abstract. This paper proposes a new heuristic algorithm suitable for real-time applications using partially observable Markov decision processes (POMDP).
Transition Entropy in Partially. Observable Markov ... A (Revised) Survey of Approximate Methods for Solving Partially Observable Markov. Decision Processes.
Abstract. This paper proposes a new heuristic algorithm suitable for real-time applications using partially observable Markov decision processes (POMDP).
In this report we describe a new POMDP algorithm, denoted TEQ-MDP, which computes the optimal policy of a modified MDP and uses the obtained optimal ...
The algorithm is based in a reward shaping strategy which includes entropy information in the reward structure of a fully observable Markov decision process ...
Abstract. In this report we describe a new POMDP algorithm, denoted TEQ-MDP, which computes the optimal policy of a modified MDP and uses the obtained ...
Abstract—We study the problem of synthesizing a controller that maximizes the entropy of a partially observable Markov decision process.
Transition entropy in partially observable Markov decision processes. Melo, F. S. & Ribeiro, M. In Proc. 9th Conf. Intelligent Autonomous Systems, pages 282 ...
May 16, 2021 · Abstract:We study the problem of synthesizing a controller that maximizes the entropy of a partially observable Markov decision process ...
A POMDP is a discrete time model of how actions influence external and observable states. From: Handbook of Statistics, 2022