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ICML
2009
IEEE
14 years 10 months ago
Monte-Carlo simulation balancing
In this paper we introduce the first algorithms for efficiently learning a simulation policy for Monte-Carlo search. Our main idea is to optimise the balance of a simulation polic...
David Silver, Gerald Tesauro
ICML
2001
IEEE
14 years 10 months ago
Direct Policy Search using Paired Statistical Tests
Direct policy search is a practical way to solve reinforcement learning problems involving continuous state and action spaces. The goal becomes finding policy parameters that maxi...
Malcolm J. A. Strens, Andrew W. Moore
ECML
2007
Springer
14 years 3 months ago
Policy Gradient Critics
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
Daan Wierstra, Jürgen Schmidhuber
ACSE
2000
ACM
14 years 1 months ago
The information environments program - a new design based IT degree
The University of Queensland has recently established a new design-focused, studio-based IT degree at a new “flexible-learning” campus. The Bachelor of Information Environment...
Michael Docherty, Peter Sutton, Margot Brereton, S...
ICCS
1993
Springer
14 years 1 months ago
Towards Domain-Independent Machine Intelligence
Adaptive predictive search (APS), is a learning system framework, which given little initial domain knowledge, increases its decision-making abilities in complex problems domains....
Robert Levinson