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» Learning Action Strategies for Planning Domains
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JAIR
2008
148views more  JAIR 2008»
13 years 6 months ago
Learning Partially Observable Deterministic Action Models
We present exact algorithms for identifying deterministic-actions' effects and preconditions in dynamic partially observable domains. They apply when one does not know the ac...
Eyal Amir, Allen Chang
CI
2010
129views more  CI 2010»
13 years 6 months ago
On-Line Case-Based Planning
Some domains, such as real-time strategy (RTS) games, pose several challenges to traditional planning and machine learning techniques. In this paper, we present a novel on-line ca...
Santi Ontañón, Kinshuk Mishra, Neha ...
ICTAI
2007
IEEE
14 years 1 months ago
Multi-agent Reinforcement Learning Using Strategies and Voting
Multiagent learning attracts much attention in the past few years as it poses very challenging problems. Reinforcement Learning is an appealing solution to the problems that arise...
Ioannis Partalas, Ioannis Feneris, Ioannis P. Vlah...
AI
1999
Springer
13 years 6 months ago
Introspective Multistrategy Learning: On the Construction of Learning Strategies
A central problem in multistrategy learning systems is the selection and sequencing of machine learning algorithms for particular situations. This is typically done by the system ...
Michael T. Cox, Ashwin Ram
AIPS
2008
13 years 9 months ago
Useless Actions Are Useful
Planning as heuristic search is a powerful approach to solving domain independent planning problems. In recent years, various successful heuristics and planners like FF, LPG, FAST...
Martin Wehrle, Sebastian Kupferschmid, Andreas Pod...