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» Opposition-Based Reinforcement Learning
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AAAI
2007
14 years 11 days ago
Active Imitation Learning
Imitation learning, also called learning by watching or programming by demonstration, has emerged as a means of accelerating many reinforcement learning tasks. Previous work has s...
Aaron P. Shon, Deepak Verma, Rajesh P. N. Rao
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
ATAL
2004
Springer
14 years 3 months ago
Best-Response Multiagent Learning in Non-Stationary Environments
This paper investigates a relatively new direction in Multiagent Reinforcement Learning. Most multiagent learning techniques focus on Nash equilibria as elements of both the learn...
Michael Weinberg, Jeffrey S. Rosenschein
ICML
1994
IEEE
14 years 1 months 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...
ACL
2010
13 years 8 months ago
Optimising Information Presentation for Spoken Dialogue Systems
We present a novel approach to Information Presentation (IP) in Spoken Dialogue Systems (SDS) using a data-driven statistical optimisation framework for content planning and attri...
Verena Rieser, Oliver Lemon, Xingkun Liu