R-FRTDP: A Real-Time DP Algorithm with Tight Bounds for a Stochastic Resource Allocation Problem

Authors:
Camille Besse;Pierrick Plamondon;Brahim Chaib-Draa
Affiliations:
Computer Science & Software Engineering Dept., Laval University, Quééébec (Qc), Canada;Computer Science & Software Engineering Dept., Laval University, Quééébec (Qc), Canada;Computer Science & Software Engineering Dept., Laval University, Quééébec (Qc), Canada
Venue:
CAI '07 Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Year:
2007

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Abstract

Resource allocation is a widely studied class of problems in Operation Research and Artificial Intelligence. Specially, constrained stochastic resource allocation problems, where the assignment of a constrained resource do not automatically imply the realization of the task. This kind of problems are generally addressed with Markov Decision Processes (mdps). In this paper, we present efficient lower and upper bounds in the context of a constrained stochastic resource allocation problem for a heuristic search algorithm called Focused Real Time Dynamic Programming (frtdp). Experiments show that this algorithm is relevant for this kind of problems and that the proposed tight bounds reduce the number of backups to perform comparatively to previous existing bounds.