Intelligent Algorithms for Maze Exploration and Exploitation-Reference-Cited by-同舟云学术

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Intelligent Algorithms for Maze Exploration and Exploitation

Published:2011-03-29 Issue: Volume: Page:
ISSN:
Container-title:Infotech@Aerospace 2011
language:
Short-container-title:

Author:

Barker Sydney¹,Sabo Chelsea¹,Cohen Kelly¹,Lafountain Cody¹

Affiliation:

1. University of Cincinnati

Publisher

American Institute of Aeronautics and Astronautics

Link

http://arc.aiaa.org/doi/pdf/10.2514/6.2011-1510

Reference5 articles.

1. 1Butler,Charles,andCaudill,Maureen,NaturallyIntelligentSystems,TheMITPress,Cambridge,Mass,2000,Chaps.2-5.

2. 2Dixon, K. R., Khosla, P. R., and Malak, R. J. "Incorporating Prior Knowledge and Previously Learned Information into Reinforcement LearningAgents,"Institutefor ComplexEngineered Systems TechnicalReportSeries,31 Jan.2000.

3. 5Kosko,B.,FuzzyThinking:TheNewScienceofFuzzyLogic,Hyperion,NewYork,1993.

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1. A Genetic Fuzzy Tree Based Moving Strategy for a Group of Nodes in Heterogeneous WSN;Lecture Notes in Electrical Engineering;2018-06-07

2. Genetic Fuzzy Trees and their Application Towards Autonomous Training and Control of a Squadron of Unmanned Combat Aerial Vehicles;Unmanned Systems;2015-07

3. Multi-agent Cooperative Decision Making using Genetic Cascading Fuzzy Systems;AIAA Infotech @ Aerospace;2015-01-02

4. Teaching Intelligent Systems at the University of Cincinnati;Infotech@Aerospace 2011;2011-03-29

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