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AAAI
2006
15 years 7 months ago
Sample-Efficient Evolutionary Function Approximation for Reinforcement Learning
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
Shimon Whiteson, Peter Stone
IC
2004
15 years 7 months ago
Improved Selective Acknowledgment Scheme for TCP
A selective acknowledgment (SACK) mechanism, combined with a selective repeat retransmission policy, has been proposed to overcome the limitations with the cumulative acknowledgme...
Rajkumar Kettimuthu, William E. Allcock
NIPS
2001
15 years 7 months ago
Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference
Estimating insurance premia from data is a difficult regression problem for several reasons: the large number of variables, many of which are discrete, and the very peculiar shape...
Nicolas Chapados, Yoshua Bengio, Pascal Vincent, J...
AAAI
1996
15 years 6 months ago
Rewarding Behaviors
Markov decision processes (MDPs) are a very popular tool for decision theoretic planning (DTP), partly because of the welldeveloped, expressive theory that includes effective solu...
Fahiem Bacchus, Craig Boutilier, Adam J. Grove
138
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NIPS
1996
15 years 6 months ago
Reinforcement Learning for Mixed Open-loop and Closed-loop Control
Closed-loop control relies on sensory feedback that is usually assumed to be free. But if sensing incurs a cost, it may be coste ective to take sequences of actions in open-loop m...
Eric A. Hansen, Andrew G. Barto, Shlomo Zilberstei...