WebOur algorithm, COptiDICE, directly estimates the stationary distribution corrections of the optimal policy with respect to returns, while constraining the cost upper bound, with the goal of yielding a cost-conservative policy for actual constraint satisfaction. WebApr 19, 2024 · Our algorithm, COptiDICE, directly estimates the stationary distribution corrections of the optimal policy with respect to returns, while constraining the cost upper bound, with the goal of yielding a cost-conservative policy for actual constraint satisfaction.
Wonseok Jeon - wsjeon.github.io
WebOptiDice TM Standard polyhedral dice optimally designed for fairness! Our designs of the standard polyhedral dice are optimized for fairness by balancing the distribution of numbers, using numerals that are physically balanced, and sizing the dice based on both manufacturing and game play considerations. WebJun 21, 2024 · Our algorithm, OptiDICE, directly estimates the stationary distribution corrections of the optimal policy and does not rely on policy-gradients, unlike previous … sign into my santander account
(PDF) COptiDICE: Offline Constrained Reinforcement Learning via ...
WebJun 21, 2024 · Our algorithm, OptiDICE, directly estimates the stationary distribution corrections of the optimal policy and does not rely on policy-gradients, unlike previous … WebOptiDICE: Offline Policy Optimization via Stationary Distribution Correction Estimation. Proceedings of the 38th International Conference on Machine Learning, in Proceedings of … WebMar 25, 2024 · As an off-policy algorithm, ValueDice is empirically shown to beat BC under the offline setting. In contrast, previous AIL algorithms (e.g., GAIL), that performs state-action distribution matching, cannot even work under the offline setting. sign in to my sbcglobal email account