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ATAL
2007
Springer
15 years 5 months ago
Batch reinforcement learning in a complex domain
Temporal difference reinforcement learning algorithms are perfectly suited to autonomous agents because they learn directly from an agent’s experience based on sequential actio...
Shivaram Kalyanakrishnan, Peter Stone
114
Voted
IJCGA
2010
155views more  IJCGA 2010»
14 years 10 months ago
Competitive Complexity of Mobile Robot on-Line Motion Planning Problems
This paper is concerned with on-line problems where a mobile robot of size D has to achieve a task in an unknown planar environment whose geometry is acquired by the robot during ...
Yoav Gabriely, Elon Rimon
86
Voted
ATAL
2005
Springer
15 years 5 months ago
Multiagent coordination by Extended Markov Tracking
We present here Extended Markov Tracking (EMT), a computationally tractable method for the online estimation of Markovian system dynamics, along with experimental support for its ...
Zinovi Rabinovich, Jeffrey S. Rosenschein
CCGRID
2007
IEEE
15 years 3 months ago
A Hybrid Linear Programming and Evolutionary Algorithm based Approach for On-line Resource Matching in Grid Environments
We describe a hybrid linear programming (LP) and evolutionary algorithm (EA) based resource matcher suitable for heterogeneous grid environments. The hybrid matcher adopts the ite...
Pawel Garbacki, Vijay K. Naik
ATAL
2007
Springer
15 years 5 months ago
Reducing the complexity of multiagent reinforcement learning
It is known that the complexity of the reinforcement learning algorithms, such as Q-learning, may be exponential in the number of environment’s states. It was shown, however, th...
Andriy Burkov, Brahim Chaib-draa