This paper considers the policy iteration problem for the challenging time-inconsistent (TIC) setting. The paper proposes backward Q-learning (bwdQ), a new ...
Mar 11, 2024 · ArticlePDF Available. Reinventing Policy Iteration under Time Inconsistency. November 2022. Authors: Nixie Sapphira Lesmana at Nanyang ...
Policy iteration (PI) is a fundamental policy search algorithm in standard reinforcement learning (RL) setting, which can be shown to converge to an optimal ...
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Reinventing Policy Iteration under Time Inconsistency. NS Lesmana, H Su, CS Pun. Transactions on Machine Learning Research, 2022. 4, 2022 ; A subgame perfect ...
Dec 17, 2020 · Policy iteration (PI) is a recursive process of policy evaluation and improvement for solving an optimal decision-making/control problem, or.
Missing: Reinventing Inconsistency.
Aug 22, 2020 · Policy iteration (PI) is a recursive process of policy evaluation and improvement for solving an optimal decision-making/control problem,.
Missing: Reinventing Inconsistency.
Nov 9, 2021 · ... In contrast, π-based. PolEva will only reflect a current iteration's changes in future policies in the next iteration,. i.e. i∗. t=i∗. t+1 + 1 ...
Reinventing Policy Iteration under Time Inconsistency. Nixie S Lesmana, Huangyuan Su, Chi Seng Pun, November 2022 [openreview] [pdf] [bib] [code] ...
Abstract. In reinforcement learning (RL), different reward functions can define the same optimal policy but result in drastically different learning perfor-.
Apr 25, 2020 · Policy iteration is a method to evaluate a value function and update a policy according to such evaluation.
Missing: Reinventing Inconsistency.