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ATAL
2005
Springer
15 years 3 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
15 years 10 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
15 years 10 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

Book
796views
16 years 9 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 4 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