Sushmita bhattacharya biography of martin
Bhattacharya works part-time, teaching the basics of English to newcomers to Britain and is also a creative writing tutor..
Sushmita Bhattacharya
In this paper we consider infinite horizon discounted dynamic programming problems with finite state and control spaces, partial state observations, and a multiagent structure.
We discuss and compare algorithms that simultaneously or sequentially optimize the agents’ controls by using multistep lookahead, truncated rollout with a known base policy, and a terminal cost function approximation.
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Our methods specifically address the computational challenges of partially observable multiagent problems. In particular: 1) We consider rollout algorithms that dramatically reduce required computation while preserving the key cost improvement property of the standard rollout method.
The per-step computational requirements for our methods are on the order of O(Cm) as compared with O(C^m) for standard rollout, where C is the maximum cardinality of the constraint set for the control component of each agent, and m is the n