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» On learning with dissimilarity functions
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AAAI
2006
13 years 10 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
COLT
1999
Springer
14 years 1 months ago
Learning Threshold Functions with Small Weights Using Membership Queries
We study the learnability of Threshold functions with bounded weights using membership queries only. We show that the class Ct of Threshold functions with positive integer weights...
Elias Abboud, Nader Agha, Nader H. Bshouty, Nizar ...
NIPS
2001
13 years 10 months ago
Rates of Convergence of Performance Gradient Estimates Using Function Approximation and Bias in Reinforcement Learning
We address two open theoretical questions in Policy Gradient Reinforcement Learning. The first concerns the efficacy of using function approximation to represent the state action ...
Gregory Z. Grudic, Lyle H. Ungar
ICML
2006
IEEE
14 years 3 months ago
Automatic basis function construction for approximate dynamic programming and reinforcement learning
We address the problem of automatically constructing basis functions for linear approximation of the value function of a Markov Decision Process (MDP). Our work builds on results ...
Philipp W. Keller, Shie Mannor, Doina Precup
ICML
2006
IEEE
14 years 10 months ago
On a theory of learning with similarity functions
Kernel functions have become an extremely popular tool in machine learning, with an attractive theory as well. This theory views a kernel as implicitly mapping data points into a ...
Maria-Florina Balcan, Avrim Blum