{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,3,30]],"date-time":"2022-03-30T12:07:45Z","timestamp":1648642065556},"reference-count":8,"publisher":"World Scientific Pub Co Pte Lt","issue":"03","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Advs. Complex Syst."],"published-print":{"date-parts":[[2003,9]]},"abstract":"<jats:p> Distillations utilize multi-agent based modeling and simulation techniques to study warfare as a complex adaptive system at the conceptual level. The focus is placed on the interactions between the agents to facilitate study of cause and effect between individual interactions and overall system behavior. Current distillations do not utilize machine-learning techniques to model the cognitive abilities of individual combatants but employ agent control paradigms to represent agents as highly instinctual entities. For a team of agents implementing a reinforcement-learning paradigm, the rate of learning is not sufficient for agents to adapt to this hostile environment. However, by allowing the agents to communicate their respective rewards for actions performed as the simulation progresses, the rate of learning can be increased sufficiently to significantly increase the teams chances of survival. This paper presents the results of trials to measure the success of a team-based approach to the reinforcement-learning problem in a distillation, using reward communication to increase learning rates. <\/jats:p>","DOI":"10.1142\/s0219525903000979","type":"journal-article","created":{"date-parts":[[2003,12,2]],"date-time":"2003-12-02T06:58:00Z","timestamp":1070348280000},"page":"405-426","source":"Crossref","is-referenced-by-count":1,"title":["EFFECTS OF COMMUNICATION ON GROUP LEARNING RATES IN A MULTI-AGENT ENVIRONMENT"],"prefix":"10.1142","volume":"06","author":[{"given":"PAUL","family":"DARBYSHIRE","sequence":"first","affiliation":[{"name":"School of Information Systems, Victoria University of Technology, PO Box 14428, Melbourne City MC, Melbourne, Victoria 8001, Australia"}]}],"member":"219","published-online":{"date-parts":[[2011,11,20]]},"reference":[{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.11610\/isij.0801"},{"key":"rf6","series-title":"Multi-agent systems","volume-title":"An Introduction to Distributed Artificial Intelligence","author":"Ferber J.","year":"1999"},{"key":"rf7","volume-title":"Simulation for the Social Scientist","author":"Gilbert N.","year":"1999"},{"key":"rf8","volume":"5","author":"Goldspink C.","journal-title":"J. Artificial Societies and Social Simulation"},{"key":"rf12","volume-title":"Land Warfare and Complexity, Part II : An Assessment of the Applicability of Non-Linear Dynamics and Complex Systems Theory to the Study of Land Warfare","author":"Ilachinski A.","year":"1996"},{"key":"rf14","volume-title":"Machine Learning","author":"Mitchell T. M.","year":"1997"},{"key":"rf17","doi-asserted-by":"publisher","DOI":"10.1080\/09515080120033599"},{"key":"rf18","volume-title":"Reinforcement Learning: An Introduction","author":"Sutton R. S.","year":"1998"}],"container-title":["Advances in Complex Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0219525903000979","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T16:25:07Z","timestamp":1565108707000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0219525903000979"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2003,9]]},"references-count":8,"journal-issue":{"issue":"03","published-online":{"date-parts":[[2011,11,20]]},"published-print":{"date-parts":[[2003,9]]}},"alternative-id":["10.1142\/S0219525903000979"],"URL":"https:\/\/doi.org\/10.1142\/s0219525903000979","relation":{},"ISSN":["0219-5259","1793-6802"],"issn-type":[{"value":"0219-5259","type":"print"},{"value":"1793-6802","type":"electronic"}],"subject":[],"published":{"date-parts":[[2003,9]]}}}