Opposition-Based Learning: A New Scheme for Machine Intelligence

Opposition-based learning as a new scheme for machine intelligence is introduced. Estimates and counter-estimates, weights and opposite weights, and actions versus counter-actions are the foundation of this new approach. Examples are provided. Possibilities for extensions of existing learning algori...

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Main Author: Tizhoosh, H.R.
Format: Conference Proceeding
Language:English
Subjects:
Biological neural networks
Computational intelligence
Genetic algorithms
Humans
Intelligent agent
Internet
Learning systems
Machine intelligence
Machine learning
Neural networks
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creator Tizhoosh, H.R.
description Opposition-based learning as a new scheme for machine intelligence is introduced. Estimates and counter-estimates, weights and opposite weights, and actions versus counter-actions are the foundation of this new approach. Examples are provided. Possibilities for extensions of existing learning algorithms are discussed. Preliminary results are provided
doi_str_mv 10.1109/CIMCA.2005.1631345
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identifier ISBN: 9780769525044
ispartof International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06), 2005, Vol.1, p.695-701
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Biological neural networks
Computational intelligence
Genetic algorithms
Humans
Intelligent agent
Internet
Learning systems
Machine intelligence
Machine learning
Neural networks
title Opposition-Based Learning: A New Scheme for Machine Intelligence
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