Fuzzy cognitive maps for decision-making in dynamic environments

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@Article{Nachazel:GPEM,

• author = "Tomas Nachazel",
• title = "Fuzzy cognitive maps for decision-making in dynamic environments",
• journal = "Genetic Programming and Evolvable Machines",
• year = "2021",
• volume = "22",
• number = "1",
• pages = "101--135",
• month = mar,
• keywords = "genetic algorithms, genetic programming, phylogenetic tree, ALife, Autonomous systems, Decision-making, Dynamic environments, Fuzzy cognitive maps, Multi-agent models",
• ISSN = "1389-2576",
• URL = "https://rdcu.be/b4w5p",
• DOI = "doi:10.1007/s10710-020-09393-2",
• size = "35 pages",
• abstract = "This paper describes a new modification of fuzzy cognitive maps (FCMs) for the modeling of autonomous entities that make decisions in a dynamic environment. The paper offers a general design for an FCM adjusted for the decision-making of autonomous agents through the categorization of its concepts into three different classes according to their purpose in the map: Needs, Activities, and States (FCM-NAS). The classification enables features supporting decision-making, such as the easy processing of input from sensors, faster system reactions, the modeling of inner needs, the adjustable frequency of computations in a simulation, and self-evaluation of the FCM-NAS that supports unsupervised evolutionary learning. This paper presents two use cases of the proposed extension to demonstrate its abilities. It was implemented into an agent-based artificial life model, where it took advantage of all the above features in the competition for resources, natural selection, and evolution. Then, it was used as decision-making for human activity simulation in an ambient intelligence model, where it is combined with scenario-oriented mechanism proving its modularity.",
• notes = "Is this GP?",

}

Genetic Programming entries for Tomas Nachazel

Citations