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ATAL
2008
Springer
13 years 9 months ago
The permutable POMDP: fast solutions to POMDPs for preference elicitation
The ability for an agent to reason under uncertainty is crucial for many planning applications, since an agent rarely has access to complete, error-free information about its envi...
Finale Doshi, Nicholas Roy
PRIMA
2007
Springer
14 years 1 months ago
Multiagent Planning with Trembling-Hand Perfect Equilibrium in Multiagent POMDPs
Multiagent Partially Observable Markov Decision Processes are a popular model of multiagent systems with uncertainty. Since the computational cost for finding an optimal joint pol...
Yuichi Yabu, Makoto Yokoo, Atsushi Iwasaki
ENTCS
2006
134views more  ENTCS 2006»
13 years 7 months ago
Partial Order Reduction for Probabilistic Branching Time
In the past, partial order reduction has been used successfully to combat the state explosion problem in the context of model checking for non-probabilistic systems. For both line...
Christel Baier, Pedro R. D'Argenio, Marcus Grö...
AI
2011
Springer
12 years 11 months ago
Decentralized MDPs with sparse interactions
In this work, we explore how local interactions can simplify the process of decision-making in multiagent systems, particularly in multirobot problems. We review a recent decision-...
Francisco S. Melo, Manuela M. Veloso
ICANN
2007
Springer
14 years 1 months ago
Solving Deep Memory POMDPs with Recurrent Policy Gradients
Abstract. This paper presents Recurrent Policy Gradients, a modelfree reinforcement learning (RL) method creating limited-memory stochastic policies for partially observable Markov...
Daan Wierstra, Alexander Förster, Jan Peters,...