In this paper, we bring techniques from operations research to bear on the problem of choosing optimal actions in partially observable stochastic domains.
In this paper, we bring techniques from operations research to bear on the problem of choosing optimal actions in partially observable stochastic domains.
People also ask
What is stochastic planning?
What is a partially observable Markov decision process?
In this paper, we bring techniques from operations research to bear on the problem of choosing optimal actions in partially observable stochastic domains.
In this paper, we bring techniques from operations research to bear on the problem of choosing optimal actions in partially observable stochastic domains.
Upper bounds on the sample complexity are proved showing that, even for infinitely large and arbitrarily complex POMDPs, the amount of data needed can be ...
In this paper, we describe the partially observable. Markov decision process (POMDP) approach to finding optimal or near-optimal control strategies for ...
Consider the problem of a robot navigating in a large office building. The robot can move from hallway intersection to intersection and can make local ...
Nov 1, 1995 · Abstract. In this paper, we bring techniques from operations research to bear on the problem of choosing optimal actions in partially ...
PDF | In this paper, we describe the partially observable Markov decision process (pomdp) approach to finding optimal or near-optimal control strategies.
In this paper, we bring techniques from operations research to bear on the problem of choosing optimal actions in partially observable stochastic domains. We ...