@article{
 title = {A Reinforcement Learning Method For An Autonomous Robot},
 type = {article},
 websites = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.53.7839},
 id = {bcfcb35d-1dda-3cb3-9859-a0e64229d3d9},
 created = {2018-07-12T01:22:14.128Z},
 accessed = {2015-04-23},
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 profile_id = {95e10851-cdf3-31de-9f82-1ab629e601b0},
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 last_modified = {2018-07-12T01:22:14.128Z},
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 authored = {false},
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 abstract = {This paper presents a fuzzy navigation system for an autonomous robot. A behavior-based control system provides the robot with the adaptibility necessary for coping with a dynamically changing environment. Moreover, a reinforcement learning method is used for on-line rule optimization.},
 bibtype = {article},
 author = {Pierre Yves Glorennec, Lionel Jouffe, Pierre Yves, Glorennec Lionel Jouffe}
}

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