Two Views on Multiple Mean-Payoff Objectives in Markov Decision Processes
| Authors | |
|---|---|
| Year of publication | 2011 |
| Type | Article in Proceedings |
| Conference | Proceedings 26th Annual IEEE Symposium on Logic in Computer Science |
| MU Faculty or unit | |
| Citation | |
| Doi | http://dx.doi.org/10.1109/LICS.2011.10 |
| Field | Informatics |
| Keywords | Markov decision process; optimization with multiple objectives; mean payoff; Pareto curve; approximation |
| Description | We study Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) functions. We consider two different objectives, namely, expectation and satisfaction objectives. Given an MDP with k reward functions, in the expectation objective the goal is to maximize the expected value, and in the satisfaction objective the goal is to maximize the probability of runs such that the limit-average value stays above a given vector. |
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