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» Markov Decision Processes with Arbitrary Reward Processes
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115
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AAAI
1994
15 years 5 months ago
Acting Optimally in Partially Observable Stochastic Domains
In this paper, we describe the partially observable Markov decision process pomdp approach to nding optimal or near-optimal control strategies for partially observable stochastic ...
Anthony R. Cassandra, Leslie Pack Kaelbling, Micha...
ICRA
2010
IEEE
101views Robotics» more  ICRA 2010»
15 years 2 months ago
Multirobot coordination by auctioning POMDPs
— We consider the problem of task assignment and execution in multirobot systems, by proposing a procedure for bid estimation in auction protocols. Auctions are of interest to mu...
Matthijs T. J. Spaan, Nelson Gonçalves, Jo&...
166
Voted
ICML
2006
IEEE
15 years 10 months ago
Automatic basis function construction for approximate dynamic programming and reinforcement learning
We address the problem of automatically constructing basis functions for linear approximation of the value function of a Markov Decision Process (MDP). Our work builds on results ...
Philipp W. Keller, Shie Mannor, Doina Precup
ICVS
2001
Springer
15 years 8 months ago
Adapting Object Recognition across Domains: A Demonstration
High-level vision systems use object, scene or domain specific knowledge to interpret images. Unfortunately, this knowledge has to be acquired for every domain. This makes it diffi...
Bruce A. Draper, Ulrike Ahlrichs, Dietrich Paulus
AAAI
2007
15 years 6 months ago
Situated Conversational Agents
A Situated Conversational Agent (SCA) is an agent that engages in dialog about the context within which it is embedded. Situated dialog is characterized by its deep connection to ...
William Thompson