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» Learning Action Selection Network of Intelligent Agent
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AAAI
1997
15 years 3 months ago
Incremental Methods for Computing Bounds in Partially Observable Markov Decision Processes
Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect ...
Milos Hauskrecht
JMLR
2012
13 years 4 months ago
Hierarchical Relative Entropy Policy Search
Many real-world problems are inherently hierarchically structured. The use of this structure in an agent’s policy may well be the key to improved scalability and higher performa...
Christian Daniel, Gerhard Neumann, Jan Peters
IAT
2010
IEEE
14 years 12 months ago
An Interactive Tool for Constrained Clustering with Human Sampling
Abstract--This paper describes an interactive tool for constrained clustering that helps users to select effective constraints efficiently during the constrained clustering process...
Masayuki Okabe, Seiji Yamada
AAAI
2011
14 years 1 months ago
Transportability of Causal and Statistical Relations: A Formal Approach
We address the problem of transferring information learned from experiments to a different environment, in which only passive observations can be collected. We introduce a formal ...
Judea Pearl, Elias Bareinboim
AAMAS
2004
Springer
15 years 1 months ago
Automated Assistants for Analyzing Team Behaviors
Multi-agent teamwork is critical in a large number of agent applications, including training, education, virtual enterprises and collective robotics. The complex interactions of ag...
Ranjit Nair, Milind Tambe, Stacy Marsella, Taylor ...