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

2015 ◽  
Author(s):  
Toma Nachazel
Keyword(s):  
Decision Making ◽  
Artificial Life ◽  
Cognitive Maps ◽  
Fuzzy Cognitive Maps ◽  
Model Based ◽  
Life Model

Artificial Life Environment Modeled by Dynamic Fuzzy Cognitive Maps

2018 ◽  
Vol 10 (1) ◽  
pp. 88-101 ◽  
Author(s):  
Lucia Valeria R. Arruda ◽  
Marcio Mendonca ◽  
Flavio Neves ◽  
Ivan Rossato Chrun ◽  
Elpiniki I. Papageorgiou
Keyword(s):  
Artificial Life ◽  
Cognitive Maps ◽  
Fuzzy Cognitive Maps

FUZZY COGNITIVE MAPS WITH GENETIC ALGORITHM FOR GOAL-ORIENTED DECISION SUPPORT

2004 ◽  
Vol 12 (supp02) ◽  
pp. 31-42 ◽  
Author(s):  
M. SHAMIM KHAN ◽  
SEBASTIAN KHOR ◽  
ALEX CHONG
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Genetic Algorithms ◽  
Decision Support ◽  
Directed Graphs ◽  
Cognitive Maps ◽  
Fuzzy Cognitive Maps ◽  
Initial State ◽  
Initial Stimulus ◽  
Over Time

Fuzzy cognitive maps are signed directed graphs used to model the evolution of scenarios with time. FCMs can be useful in decision support for predicting future states given an initial state. Genetic algorithms (GA) are well-established tools for optimization. This paper concerns the use of FCMs in goal-directed analysis of scenarios for aiding decision making. A methodology for GA-based goal-directed analysis is presented. The search for the initial stimulus state, that over time leads to a target state of interest, is optimized using GA. This initial state found can be used to answer the question – what course of events leads to a certain state in a given scenario?

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