There is an ever increasing number of sources that may be used for knowledge processing. Often this requires dealing with heterogeneous knowledge and current methods become inadequate in these tasks. Thus it becomes important to develop better general methods and tools, or methods tailored to specific problems. In this paper we consider the problem of knowledge integration in a group of social agents. We use approaches based on particle swarm optimization – without the optimization component – to model the diffusion of information in a group of social agents. We present a short description of the theoretical model – a modification of PSO heuristics. We also conduct an experiment comparing this approach to previously researched models of knowledge integration in a group of social agents.
CITATION STYLE
Maleszka, M. (2017). Particle Swarm of Agents for Heterogenous Knowledge Integration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10448 LNAI, pp. 54–62). Springer Verlag. https://doi.org/10.1007/978-3-319-67074-4_6
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