Connectionist Learning in Behaviour-Based Mobile Robots: A Survey

作者:Mark Rylatt, Chris Czarnecki, Tom Routen

摘要

This paper is a survey of some recentconnectionist approaches to the design and developmentof behaviour-based mobile robots. The research isanalysed in terms of principal connectionist learningmethods and neurological modeling trends. Possibleadvantages over conventionally programmed methods areconsidered and the connectionist achievements to dateare assessed. A realistic view is taken of theprospects for medium term progress and someobservations are made concerning the direction thismight profitably take.

论文关键词:architectures for autonomous robots, artificial neural networks, behaviour-based robots, emergent properties, reinforcement learning, supervised learning, unsupervised learning

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论文官网地址:https://doi.org/10.1023/A:1006567623867