Optimization of Decision-Making in Artificial Life Model Based on Fuzzy Cognitive Maps

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F15%3A50003677" target="_blank" >RIV/62690094:18450/15:50003677 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/IE.2015.28" target="_blank" >http://dx.doi.org/10.1109/IE.2015.28</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IE.2015.28" target="_blank" >10.1109/IE.2015.28</a>

Result language
angličtina
Original language name
Optimization of Decision-Making in Artificial Life Model Based on Fuzzy Cognitive Maps
Original language description
The paper describes a new approach to the modeling of the individual-based artificial life model based on fuzzy cognitive maps (FCM). The proposed concept focuses on the optimization of artificial intelligence of individuals in multi-agent models and their adaptation to environment. In this process of optimization, emphasis is put on the decision-making method. FCM offers great complexity and learning through evolutionary algorithms. However, too large FCMs suffer from performance issues. Therefore, this paper presents a possibility to replace a decision-making part of large FCM with the analytic hierarchy process (AHP) method, which is widely used, Eespecially for decision support. In comparison with the large FCM model, a combination with AHP provides a model with lower computational demands while keeping nearly the same complexity.
Czech name
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Czech description
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Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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