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NIPS
2001
13 years 9 months ago
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
Evan Greensmith, Peter L. Bartlett, Jonathan Baxte...
NIPS
2001
13 years 9 months ago
Multiagent Planning with Factored MDPs
We present a principled and efficient planning algorithm for cooperative multiagent dynamic systems. A striking feature of our method is that the coordination and communication be...
Carlos Guestrin, Daphne Koller, Ronald Parr
IJCAI
2003
13 years 9 months ago
Approximating Optimal Policies for Agents with Limited Execution Resources
An agent with limited consumable execution resources needs policies that attempt to achieve good performance while respecting these limitations. Otherwise, an agent (such as a pla...
Dmitri A. Dolgov, Edmund H. Durfee
SODA
2004
ACM
94views Algorithms» more  SODA 2004»
13 years 9 months ago
Quantitative stochastic parity games
We study perfect-information stochastic parity games. These are two-player nonterminating games which are played on a graph with turn-based probabilistic transitions. A play resul...
Krishnendu Chatterjee, Marcin Jurdzinski, Thomas A...
NIPS
2003
13 years 9 months ago
Distributed Optimization in Adaptive Networks
We develop a protocol for optimizing dynamic behavior of a network of simple electronic components, such as a sensor network, an ad hoc network of mobile devices, or a network of ...
Ciamac Cyrus Moallemi, Benjamin Van Roy