Flexible optimization and evolution of underwater autonomous agents

E. Eberbach; R. Brooks; S. Phoha

doi:10.1007/978-3-540-48061-7_64

Flexible optimization and evolution of underwater autonomous agents

E. Eberbach
, R. Brooks
, S. Phoha

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

8 Scopus citations

Abstract

The “Ocean SAmpling MObile Network” (SAMON) Project is a simulation testbed for Web-based interaction among oceanographers and simulation based design of Ocean Sampling missions. In this paper, the current implementation of SAMON is presented, along with a formal model based on process algebra. Flexible optimization handles planning, mobility, evolution, and learning. A generic behavior message-passing language is developed for communication and knowledge representation among heterogeneous Autonomous Undersea Vehicles (AUV's). The process algebra subsumed in this language expresses a generalized optimization framework that contains genetic algorithms, and neural networks as limiting cases.

Original language	English (US)
Title of host publication	New Directions in Rough Sets, Data Mining, and Granular-Soft Computing - 7th International Workshop, RSFDGrC 1999, Proceedings
Editors	Setsuo Ohsuga, Ning Zhong, Andrzej Skowron
Publisher	Springer Verlag
Pages	519-527
Number of pages	9
ISBN (Print)	3540666451, 9783540666455
DOIs	https://doi.org/10.1007/978-3-540-48061-7_64
State	Published - 1999
Event	7th International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing, RSFDGrC 1999 - Yamaguchi, Japan Duration: Nov 9 1999 → Nov 11 1999

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	1711
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	7th International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing, RSFDGrC 1999
Country/Territory	Japan
City	Yamaguchi
Period	11/9/99 → 11/11/99

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-540-48061-7_64

Cite this

Eberbach, E., Brooks, R., & Phoha, S. (1999). Flexible optimization and evolution of underwater autonomous agents. In S. Ohsuga, N. Zhong, & A. Skowron (Eds.), New Directions in Rough Sets, Data Mining, and Granular-Soft Computing - 7th International Workshop, RSFDGrC 1999, Proceedings (pp. 519-527). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1711). Springer Verlag. https://doi.org/10.1007/978-3-540-48061-7_64

Eberbach, E. ; Brooks, R. ; Phoha, S. / Flexible optimization and evolution of underwater autonomous agents. New Directions in Rough Sets, Data Mining, and Granular-Soft Computing - 7th International Workshop, RSFDGrC 1999, Proceedings. editor / Setsuo Ohsuga ; Ning Zhong ; Andrzej Skowron. Springer Verlag, 1999. pp. 519-527 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "The “Ocean SAmpling MObile Network” (SAMON) Project is a simulation testbed for Web-based interaction among oceanographers and simulation based design of Ocean Sampling missions. In this paper, the current implementation of SAMON is presented, along with a formal model based on process algebra. Flexible optimization handles planning, mobility, evolution, and learning. A generic behavior message-passing language is developed for communication and knowledge representation among heterogeneous Autonomous Undersea Vehicles (AUV's). The process algebra subsumed in this language expresses a generalized optimization framework that contains genetic algorithms, and neural networks as limiting cases.",

author = "E. Eberbach and R. Brooks and S. Phoha",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 1999. Copyright: Copyright 2016 Elsevier B.V., All rights reserved.; 7th International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing, RSFDGrC 1999 ; Conference date: 09-11-1999 Through 11-11-1999",

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Eberbach, E, Brooks, R & Phoha, S 1999, Flexible optimization and evolution of underwater autonomous agents. in S Ohsuga, N Zhong & A Skowron (eds), New Directions in Rough Sets, Data Mining, and Granular-Soft Computing - 7th International Workshop, RSFDGrC 1999, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1711, Springer Verlag, pp. 519-527, 7th International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing, RSFDGrC 1999, Yamaguchi, Japan, 11/9/99. https://doi.org/10.1007/978-3-540-48061-7_64

Flexible optimization and evolution of underwater autonomous agents. / Eberbach, E.; Brooks, R.; Phoha, S.
New Directions in Rough Sets, Data Mining, and Granular-Soft Computing - 7th International Workshop, RSFDGrC 1999, Proceedings. ed. / Setsuo Ohsuga; Ning Zhong; Andrzej Skowron. Springer Verlag, 1999. p. 519-527 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1711).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Phoha, S.

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N2 - The “Ocean SAmpling MObile Network” (SAMON) Project is a simulation testbed for Web-based interaction among oceanographers and simulation based design of Ocean Sampling missions. In this paper, the current implementation of SAMON is presented, along with a formal model based on process algebra. Flexible optimization handles planning, mobility, evolution, and learning. A generic behavior message-passing language is developed for communication and knowledge representation among heterogeneous Autonomous Undersea Vehicles (AUV's). The process algebra subsumed in this language expresses a generalized optimization framework that contains genetic algorithms, and neural networks as limiting cases.

AB - The “Ocean SAmpling MObile Network” (SAMON) Project is a simulation testbed for Web-based interaction among oceanographers and simulation based design of Ocean Sampling missions. In this paper, the current implementation of SAMON is presented, along with a formal model based on process algebra. Flexible optimization handles planning, mobility, evolution, and learning. A generic behavior message-passing language is developed for communication and knowledge representation among heterogeneous Autonomous Undersea Vehicles (AUV's). The process algebra subsumed in this language expresses a generalized optimization framework that contains genetic algorithms, and neural networks as limiting cases.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Eberbach E, Brooks R, Phoha S. Flexible optimization and evolution of underwater autonomous agents. In Ohsuga S, Zhong N, Skowron A, editors, New Directions in Rough Sets, Data Mining, and Granular-Soft Computing - 7th International Workshop, RSFDGrC 1999, Proceedings. Springer Verlag. 1999. p. 519-527. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-48061-7_64

Flexible optimization and evolution of underwater autonomous agents

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