PPSN - ENAS 2008 WORKSHOP
September 13, 2008
Technische Universität Dortmund, Germany
(See PPSN information at: http://ls11-www.cs.uni-dortmund.de/ppsn/ppsn10/ )
NOTE: PPSN - ENAS 2008 follows GECCO - ENAS 2007 Workshop
(See GECCO - ENAS 2007 information at: http://www.sigevo.org/gecco-2007/workshop-enas07.htm )
Amiram (Ami) Moshaiov
Carlos A. Coello Coello
Multi-competence Adaptation in Natural and Artificial Systems: Tradeoffs in evolution, learning and development
The aim of this workshop is to understand the similarities and dissimilarities between bio-inspired and bio-plausible multi-competence adaptation.
NOTE - We use the term multi-competence interchangeably with multi-objective to encompass both natural and artificial adaptation processes.
Comparing nature and the artificial has been proven to be fruitful for both bio-inspired design and decision making, as well as for scientific studies of nature. Well known examples of the former are soft computing methods and bio-inspired robotics, whereas the use of bio-morphs to study "the blind watchmaker" is a well-known example of the latter. Here, the focus of comparison is on tradeoffs. Despite of the notions of 'fitness' and 'performance' often being considered closely related, the idea of 'Pareto-front,' which helps engineers to investigate tradeoffs among design objectives, may appear strange or irrelevant to most biologists. Nevertheless, tradeoffs are neither new to biologists, nor to cognitive scientists.
Bio-inspired and bio-plausible parallel processing may be particularly useful in attempts to understand the nature of evolution tradeoffs and the degree to which evolution involves a "balance" between selection for multiple objectives. Or, in more general terms, such computational tools could support the study of multi-competence adaptation in natural and artificial systems. Evolution, learning, and development could be considered as influencing adaptation in different time scales. Hence we seek to understand the role of tradeoffs in such individual modes of adaptation as well as in their combined situations. We further want to explore, which are the most fundamental tradeoffs in natural adaptation, and in engineering design. Some more detailed information is given below.
Metaphors and analogies in EC and in particular as related to MOEA
Similarities and dissimilarities between natural and artificial processes of adaptation
The adaptation/optimization debate and its relation to teleology and the notion of objectives
Tradeoffs in natural systems and their comparison with tradeoffs in engineering design and in multi-criteria decision making
Tradeoffs in conceptual design and in natural "concepts" such as species
Tradeoffs in co-evolution and in game theory
Tradeoffs in computational methods including: Neural Networks, EC, Fuzzy Logic, Organic Computing, Bio-inspired hybrid metaheuristics, DNA Computing, Quantum Computing, among others.
Tradeoffs in application areas such as: Control, Robotics, A-life, Complexity Science, Informatics, Environmental planning, Economics, Social Sciences, Cognitive and Behavioral Sciences,
A note on application areas and computational methods:
Contributions on any application areas and computational methods are welcome provided that a discussion is included on the related aspects of multi-competence adaptation in natural and artificial systems.
Format of Contributions:
Submissions could be either as white papers, extended abstracts, or full papers.
For submission details please contact Ami Moshaiov at: firstname.lastname@example.org
Half a day