A unified framework for symbiosis of evolutionary mechanisms with application to water clusters potential model design

IEEE Computational Intelligence Magazine

Volumn 7, Issue 1, 2012, Pages 20-35

  Le, Minh Nghia ^a   Ong, Yew Soon ^a   Jin, Yaochu ^b   Sendhoff, Bernhard ^c  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b UNIVERSITY OF SURREY   (United Kingdom)

^c HONDA RESEARCH INSTITUTE EUROPE GMBH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE SEARCH; EMPIRICAL STUDIES; EVOLUTIONARY MECHANISMS; EVOLVABILITY; LIFETIME LEARNING; POTENTIAL MODEL; SELF CONFIGURATION; STATISTICAL LEARNING; STOCHASTIC VARIATION; SYMBIOTIC EVOLUTION; THEORETIC MODEL; UNIFIED FRAMEWORK; UNSOLVED PROBLEMS; WATER CLUSTER; WATER MODELS;

ADAPTIVE ALGORITHMS; GENES; STOCHASTIC MODELS;

DESIGN;

EID: 84856365876     PISSN: 1556603X     EISSN: None     Source Type: Journal    
DOI: 10.1109/MCI.2011.2176995     Document Type: Article

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