Sushmita bhattacharya biography channel

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.

Sushmita bhattacharya biography channel

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