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» Probabilistic policy reuse in a reinforcement learning agent
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AINA
2006
IEEE
14 years 11 days ago
Constrained Flooding: A Robust and Efficient Routing Framework for Wireless Sensor Networks
Flooding protocols for wireless networks in general have been shown to be very inefficient and therefore are mainly used in network initialization or route discovery and maintenan...
Ying Zhang, Markus P. J. Fromherz
EWRL
2008
13 years 10 months ago
Markov Decision Processes with Arbitrary Reward Processes
Abstract. We consider a control problem where the decision maker interacts with a standard Markov decision process with the exception that the reward functions vary arbitrarily ove...
Jia Yuan Yu, Shie Mannor, Nahum Shimkin
IJCAI
2003
13 years 10 months ago
Simultaneous Adversarial Multi-Robot Learning
Multi-robot learning faces all of the challenges of robot learning with all of the challenges of multiagent learning. There has been a great deal of recent research on multiagent ...
Michael H. Bowling, Manuela M. Veloso
ICML
1994
IEEE
14 years 3 days ago
Learning Without State-Estimation in Partially Observable Markovian Decision Processes
Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much ...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...
IROS
2006
IEEE
107views Robotics» more  IROS 2006»
14 years 2 months ago
Heterogeneous and Hierarchical Cooperative Learning via Combining Decision Trees
Abstract— Decision trees, being human readable and hierarchically structured, provide a suitable mean to derive state-space abstraction and simplify the inclusion of the availabl...
Masoud Asadpour, Majid Nili Ahmadabadi, Roland Sie...