The Simple Genetic Algorithm: Foundations and Theory
The Simple Genetic Algorithm: Foundations and Theory
Artficial Immune Systems and Their Applications
Artficial Immune Systems and Their Applications
A Roadmap of Agent Research and Development
Autonomous Agents and Multi-Agent Systems
Agent-Oriented Model of Simulated Evolution
SOFSEM '02 Proceedings of the 29th Conference on Current Trends in Theory and Practice of Informatics: Theory and Practice of Informatics
Design of Security System Based on Immune System
WETICE '01 Proceedings of the 10th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises
Evolutionary computation: comments on the history and current state
IEEE Transactions on Evolutionary Computation
Software agents mobility using process migration mechanism in distributed Erlang
Proceedings of the twelfth ACM SIGPLAN workshop on Erlang
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The model for the biologically inspired agent-based computation systems EMAS and iEMAS conformed to BDI standard is presented. System dynamics was modeled as the stationary Markov chain. The space of states and transition functions were identified. The probability transition of the whole system is composed of the conditional transitions caused by the particular actions. Such a model allows for better understanding the behavior of the proposed complex systems as well as their limitations. Because no constraint for the total number of agents was introduced, the model express the behavior of maximum configuration of the systems. Therefore it plays the similar role to the SGA infinite population model introduced by Vose. The sample application of iEMAS to the difficult global optimization problem (optimization of the artificial neural network architecture) showing its efficiency was also attached.