Evolved communication strategies and emergent behaviour of multi-agents in pursuit domains

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Grossi:2017:CIG,

• author = "Gina Grossi and Brian J. Ross",
• title = "Evolved communication strategies and emergent behaviour of multi-agents in pursuit domains",
• booktitle = "IEEE Conference on Computational Intelligence and Games, CIG 2017",
• year = "2017",
• pages = "110--117",
• address = "New York, NY, USA",
• month = "22-25 " # aug,
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming, multi-agent system, pursuit domain, communication, co-operative learning, emergent behaviour, video games",
• URL = "http://www.cig2017.com/wp-content/uploads/2017/08/paper_1.pdf",
• DOI = "doi:10.1109/CIG.2017.8080423",
• size = "8 pages",
• abstract = "This study investigates how genetic programs can be effectively used in a multi-agent system to allow agents to learn to communicate. Using the pursuit domain and a co-operative learning strategy, communication protocols are compared as multiple predator agents learn the meaning of commands in order to achieve their common goal of first finding and then tracking prey. The outcome of this study reveals a general synchronization behaviour emerging from simple message passing among agents. An additional outcome shows a learned behaviour in the best result which resembles the behaviour of guards and reinforcements that can be found in popular stealth video games.",
• notes = "also know as \cite{8080423}",

}

Genetic Programming entries for Gina Grossi Brian J Ross

Citations