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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Transferring knowledge as heuristics in reinforcement learning: A case-based approach

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Author(s):
Bianchi, Reinaldo A. C. [1] ; Celiberto, Jr., Luiz A. [2] ; Santos, Paulo E. [1] ; Matsuura, Jackson P. [3] ; Lopez de Mantaras, Ramon [4]
Total Authors: 5
Affiliation:
[1] Ctr Univ FEI, BR-09850901 Sao Paulo - Brazil
[2] Univ Fed ABC UFABC, Ctr Engn Modelagem & Ciencias Sociais Aplicadas C, BR-09210580 Sao Paulo - Brazil
[3] Technol Inst Aeronaut ITA, BR-12228900 Sao Paulo - Brazil
[4] CSIC, IIIA Artificial Intelligence Res Inst, Spanish Natl Res Council, Bellaterra 08193, Catalonia - Spain
Total Affiliations: 4
Document type: Journal article
Source: ARTIFICIAL INTELLIGENCE; v. 226, p. 102-121, SEP 2015.
Web of Science Citations: 24
Abstract

The goal of this paper is to propose and analyse a transfer learning meta-algorithm that allows the implementation of distinct methods using heuristics to accelerate a Reinforcement Learning procedure in one domain (the target) that are obtained from another (simpler) domain (the source domain). This meta-algorithm works in three stages: first, it uses a Reinforcement Learning step to learn a task on the source domain, storing the knowledge thus obtained in a case base; second, it does an unsupervised mapping of the source-domain actions to the target-domain actions; and, third, the case base obtained in the first stage is used as heuristics to speed up the learning process in the target domain. A set of empirical evaluations were conducted in two target domains: the 3D mountain car (using a learned case base from a 2D simulation) and stability learning for a humanoid robot in the Robocup 3D Soccer Simulator (that uses knowledge learned from the Acrobot domain). The results attest that our transfer learning algorithm outperforms recent heuristically-accelerated reinforcement learning and transfer learning algorithms. (C) 2015 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 11/19280-8 - CogBot: integrating perceptual information and semantic knowledge in cognitive robotics
Grantee:Anna Helena Reali Costa
Support Opportunities: Regular Research Grants
FAPESP's process: 12/04089-3 - Collaborative spatial reasoning for a multi-robot system
Grantee:Paulo Eduardo Santos
Support Opportunities: Regular Research Grants
FAPESP's process: 12/14010-5 - Transfer Learning to Heterogeneous Robotics
Grantee:Luiz Antonio Celiberto Junior
Support Opportunities: Scholarships in Brazil - Post-Doctoral