Proceedings of the 9th annual conference on Genetic and evolutionary computation
Graph structured program evolution
Proceedings of the 9th annual conference on Genetic and evolutionary computation
A portfolio optimization model using Genetic Network Programming with control nodes
Expert Systems with Applications: An International Journal
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
A genetic network programming with learning approach for enhanced stock trading model
Expert Systems with Applications: An International Journal
Understanding decision-support effectiveness: a computer simulation approach
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special section: Best papers from the 2007 biometrics: Theory, applications, and systems (BTAS 07) conference
Constructing portfolio investment strategy based on time adapting genetic network programming
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Generalized time related sequential association rule mining and traffic prediction
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
A model of portfolio optimization using time adapting genetic network programming
Computers and Operations Research
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
A method of association rule analysis for incomplete database using genetic network programming
Proceedings of the 12th annual conference on Genetic and evolutionary computation
A novel evolutionary method to search interesting association rules by keywords
Expert Systems with Applications: An International Journal
Symbiogenesis as a mechanism for building complex adaptive systems: a review
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
Association rule mining with chi-squared test using alternate genetic network programming
ICDM'06 Proceedings of the 6th Industrial Conference on Data Mining conference on Advances in Data Mining: applications in Medicine, Web Mining, Marketing, Image and Signal Mining
An evolutionary approach to rank class association rules with feedback mechanism
Expert Systems with Applications: An International Journal
Environmental framework to visualize emergent artificial forest ecosystems
Information Sciences: an International Journal
EvoGeneSys, a new evolutionary approach to graph generation
Applied Soft Computing
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Multiagent Systems with Symbiotic Learning and Evolution (Masbiole) has been proposed and studied, which is a new methodology of Multiagent Systems (MAS) based on symbiosis in the ecosystem. Masbiole employs a method of symbiotic learning and evolution where agents can learn or evolve according to their symbiotic relations toward others, i.e., considering the benefits/losses of both itself and an opponent. As a result, Masbiole can escape from Nash Equilibria and obtain better performances than conventional MAS where agents consider only their own benefits. This paper focuses on the evolutionary model of Masbiole, and its characteristics are examined especially with an emphasis on the behaviors of agents obtained by symbiotic evolution. In the simulations, two ideas suitable for the effective analysis of such behaviors are introduced; "Match Type Tile-world (MTT)" and "Genetic Network Programming (GNP)". MTT is a virtual model where tile-world is improved so that agents can behave considering their symbiotic relations. GNP is a newly developed evolutionary computation which has the directed graph type gene structure and enables to analyze the decision making mechanism of agents easily. Simulation results show that Masbiole can obtain various kinds of behaviors and better performances than conventional MAS in MTT by evolution.