Leszek Siwik

Learn More
Co-evolutionary techniques for evolutionary algorithms are aimed at overcoming their limited adaptive capabilities and allow for the application of such algorithms to problems for which it is difficult or even impossible to formulate explicit fitness function. In this paper the idea of co-evolutionary multi-agent system with host-parasite mechanism for(More)
— Co-evolutionary techniques for evolutionary algorithms are aimed at overcoming their limited adaptive capabilities and allow for the application of such algorithms to problems for which it is difficult or even impossible to formulate explicit fitness function. Sexual selection resulting from sexual conflict and co-evolution of female mate choice and male(More)
Co-evolutionary techniques for evolutionary algorithms help overcoming limited adaptive capabilities of evolutionary algorithms, and maintaining population diversity. In this paper the idea and formal model of agent-based realization of predator-prey co-evolutionary algorithm is presented. The presented system is applied to the problem of effective(More)
Co-evolutionary techniques for evolutionary algorithms help overcoming limited adaptive capabilities of evolutionary algorithms, and maintaining population diversity. In this paper the idea and formal model of agent-based realization of predator-prey co-evolutionary algorithm is presented. The effect of using such approach is not only the location of Pareto(More)
— Evolutionary algorithms are (meta-)heuristic techniques used in the case of search, optimization, and adaptation problems, which cannot be solved with the use of traditional methods. Sexual selection mechanism helps to maintain the population diversity in evolutionary algorithms. In this paper the agent-based realization of multi-objective evolutionary(More)
Representing knowledge with the use of ontology description languages offers several advantages arising from knowledge reusability, possibilities of carrying out reasoning processes and the use of existing concepts of knowledge integration. In this work we are going to present an environment for the integration of knowledge expressed in such a way.(More)
The complexity of generating investment strategies makes it hard (or even impossible), in most cases, to use traditional techniques and to find the exact solution. In this chapter the evolutionary system for generating investment strategies is presented. The algorithms used in the system (evolutionary algorithm, co-evolutionary algorithm, and agent-based(More)
Co-evolutionary techniques makes it possible to apply evolutionary algorithms in the cases when it is not possible to formulate explicit fitness function. In the case of social and economic simulations such techniques provide us tools for modeling interactions between social and economic agents—especially when agent-based models of co-evolution are used. In(More)