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ICTAI
2006
IEEE
16 years 21 days ago
Polynomial Regression with Automated Degree: A Function Approximator for Autonomous Agents
In order for an autonomous agent to behave robustly in a variety of environments, it must have the ability to learn approximations to many different functions. The function approx...
Daniel Stronger, Peter Stone
ISAAC
2004
Springer
141views Algorithms» more  ISAAC 2004»
16 years 1 days ago
Weighted Coloring on Planar, Bipartite and Split Graphs: Complexity and Improved Approximation
We study complexity and approximation of min weighted node coloring in planar, bipartite and split graphs. We show that this problem is NP-complete in planar graphs, even if they a...
Jérôme Monnot, Vangelis Th. Paschos, ...
AAAI
2006
15 years 8 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
WADS
2005
Springer
132views Algorithms» more  WADS 2005»
16 years 4 days ago
Communication-Aware Processor Allocation for Supercomputers
Abstract. We give processor-allocation algorithms for grid architectures, where the objective is to select processors from a set of available processors to minimize the average num...
Michael A. Bender, David P. Bunde, Erik D. Demaine...
CDC
2010
IEEE
160views Control Systems» more  CDC 2010»
15 years 1 months ago
Adaptive bases for Q-learning
Abstract-- We consider reinforcement learning, and in particular, the Q-learning algorithm in large state and action spaces. In order to cope with the size of the spaces, a functio...
Dotan Di Castro, Shie Mannor