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AAAI
2006
13 years 9 months ago
Using Homomorphisms to Transfer Options across Continuous Reinforcement Learning Domains
We examine the problem of Transfer in Reinforcement Learning and present a method to utilize knowledge acquired in one Markov Decision Process (MDP) to bootstrap learning in a mor...
Vishal Soni, Satinder P. Singh
ATAL
2008
Springer
13 years 9 months ago
Sequential decision making in repeated coalition formation under uncertainty
The problem of coalition formation when agents are uncertain about the types or capabilities of their potential partners is a critical one. In [3] a Bayesian reinforcement learnin...
Georgios Chalkiadakis, Craig Boutilier
GECCO
2004
Springer
106views Optimization» more  GECCO 2004»
14 years 1 months ago
Run Transferable Libraries - Learning Functional Bias in Problem Domains
Abstract. This paper introduces the notion of Run Transferable Libraries, a mechanism to pass knowledge acquired in one GP run to another. We demonstrate that a system using these ...
Maarten Keijzer, Conor Ryan, Mike Cattolico
ATAL
2009
Springer
14 years 2 months ago
Transfer via soft homomorphisms
The field of transfer learning aims to speed up learning across multiple related tasks by transferring knowledge between source and target tasks. Past work has shown that when th...
Jonathan Sorg, Satinder Singh
AGI
2008
13 years 9 months ago
Transfer Learning and Intelligence: an Argument and Approach
In order to claim fully general intelligence in an autonomous agent, the ability to learn is one of the most central capabilities. Classical machine learning techniques have had ma...
Matthew E. Taylor, Gregory Kuhlmann, Peter Stone