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» Algorithms for Inverse Reinforcement Learning
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ICML
2005
IEEE
14 years 11 months ago
Learning to compete, compromise, and cooperate in repeated general-sum games
Learning algorithms often obtain relatively low average payoffs in repeated general-sum games between other learning agents due to a focus on myopic best-response and one-shot Nas...
Jacob W. Crandall, Michael A. Goodrich
ATAL
2009
Springer
14 years 4 months ago
Online exploration in least-squares policy iteration
One of the key problems in reinforcement learning is balancing exploration and exploitation. Another is learning and acting in large or even continuous Markov decision processes (...
Lihong Li, Michael L. Littman, Christopher R. Mans...
JCP
2008
139views more  JCP 2008»
13 years 10 months ago
Agent Learning in Relational Domains based on Logical MDPs with Negation
In this paper, we propose a model named Logical Markov Decision Processes with Negation for Relational Reinforcement Learning for applying Reinforcement Learning algorithms on the ...
Song Zhiwei, Chen Xiaoping, Cong Shuang
ICML
2001
IEEE
14 years 11 months ago
Off-Policy Temporal Difference Learning with Function Approximation
We introduce the first algorithm for off-policy temporal-difference learning that is stable with linear function approximation. Off-policy learning is of interest because it forms...
Doina Precup, Richard S. Sutton, Sanjoy Dasgupta
HIS
2008
13 years 11 months ago
New Crossover Operator for Evolutionary Rule Discovery in XCS
XCS is a learning classifier system that combines a reinforcement learning scheme with evolutionary algorithms to evolve rule sets on-line by means of the interaction with an envi...
Sergio Morales-Ortigosa, Albert Orriols-Puig, Este...