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

Abstract

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, especially 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. Keywords-fuzzy cognitive maps; analytic hierarchy process; artificial life; individual-based; multi-agent model; decisionmaking2015 International Conference on Intelligent Environments 978-1-4673-6654-0/15 $31.00

A hybrid FCM-AHP approach to predict impacts of offshore outsourcing location decisions on supply chain resilience

“…Concerning the driving force B, FCM allows to calculate local and/or global weights to be used in TOPSIS, AHP and ANP to assess alternatives (Baykasoğlu & Gölcük, 2015;Nachazel, 2015;Yu & Tzeng, 2006). FCM thus overcomes the problem of interdependence among criteria, as well as the problem of hard questions derived from pairwise comparison.…”

“…A FCM calculates the attribute weights To be used in TOPSIS to rank alternatives (Nachazel, 2015) Decision-making in artificial life AHP and FCM A FCM estimates the weights of criteria used to determine which activity should individual choose with AHP (Kang, Zhang, & Bai, 2016) Evaluation of the oil-spill emergency response capability AHP and FCM B FCM and AHP determine the weights in first and second levels of the distribution model, respectively.…”