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273views
13 years 5 months ago
Monte Carlo Value Iteration for Continuous-State POMDPs
Partially observable Markov decision processes (POMDPs) have been successfully applied to various robot motion planning tasks under uncertainty. However, most existing POMDP algo...
Haoyu Bai, David Hsu, Wee Sun Lee, and Vien A. Ngo
ATAL
2008
Springer
13 years 12 months ago
Reinforcement learning for DEC-MDPs with changing action sets and partially ordered dependencies
Decentralized Markov decision processes are frequently used to model cooperative multi-agent systems. In this paper, we identify a subclass of general DEC-MDPs that features regul...
Thomas Gabel, Martin A. Riedmiller
ICTAI
2007
IEEE
14 years 4 months ago
Multi-criteria Decision Making for Local Coordination in Multi-agent Systems
Unlike mono-agent systems, multi-agent planing addresses the problem of resolving conflicts between individual and group interests. In this paper, we are using a Decentralized Ve...
Matthieu Boussard, Maroua Bouzid, Abdel-Illah Moua...
CORR
2010
Springer
112views Education» more  CORR 2010»
13 years 10 months ago
Efficient Approximation of Optimal Control for Markov Games
The success of probabilistic model checking for discrete-time Markov decision processes and continuous-time Markov chains has led to rich academic and industrial applications. The ...
Markus Rabe, Sven Schewe, Lijun Zhang
SIGECOM
2009
ACM
114views ECommerce» more  SIGECOM 2009»
14 years 4 months ago
Policy teaching through reward function learning
Policy teaching considers a Markov Decision Process setting in which an interested party aims to influence an agent’s decisions by providing limited incentives. In this paper, ...
Haoqi Zhang, David C. Parkes, Yiling Chen