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ATAL
2005
Springer
15 years 8 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
ICML
2001
IEEE
16 years 3 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
ICML
2004
IEEE
16 years 3 months ago
Apprenticeship learning via inverse reinforcement learning
We consider learning in a Markov decision process where we are not explicitly given a reward function, but where instead we can observe an expert demonstrating the task that we wa...
Pieter Abbeel, Andrew Y. Ng
217
Voted

Book
796views
17 years 1 months ago
Introduction to Machine Learning
This is an introductory book about machine learning. Notice that this is a draft book. It may contain typos, mistakes, etc. The book covers the following topics: Boolean Functio...
Nils J. Nilsson
APPROX
2007
Springer
112views Algorithms» more  APPROX 2007»
15 years 8 months ago
Encouraging Cooperation in Sharing Supermodular Costs
Abstract Consider a situation where a group of agents wishes to share the costs of their joint actions, and needs to determine how to distribute the costs amongst themselves in a f...
Andreas S. Schulz, Nelson A. Uhan