Search Results for author: Yash Satsangi

Found 5 papers, 0 papers with code

Useful Policy Invariant Shaping from Arbitrary Advice

no code implementations2 Nov 2020 Paniz Behboudian, Yash Satsangi, Matthew E. Taylor, Anna Harutyunyan, Michael Bowling

Furthermore, if the reward is constructed from a potential function, the optimal policy is guaranteed to be unaltered.

Exploiting Submodular Value Functions For Scaling Up Active Perception

no code implementations21 Sep 2020 Yash Satsangi, Shimon Whiteson, Frans A. Oliehoek, Matthijs T. J. Spaan

Furthermore, we show that, under certain conditions, including submodularity, the value function computed using greedy PBVI is guaranteed to have bounded error with respect to the optimal value function.

Maximizing Information Gain in Partially Observable Environments via Prediction Reward

no code implementations11 May 2020 Yash Satsangi, Sungsu Lim, Shimon Whiteson, Frans Oliehoek, Martha White

Information gathering in a partially observable environment can be formulated as a reinforcement learning (RL), problem where the reward depends on the agent's uncertainty.

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