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• W128152812 abstract "H. Mostafahalamostafa@hotmail.comR. Bahgatrbahgat@rite.comDept. of Computer Science, Faculty of Computers & InformationCairo University, Cairo - EgyptF. Holmgrenfredrikh@sics.seDistributed Systems Laboratory, Swedish Institute of Computer Science (SICS),SwedenAbstract In this paper, we propose a multi-agent system (MAS)to simulate a community of beings that move, eat,reproduce, trade and auction, among other activities. Wedemonstrate how beings using primitive rules result inemerging, non-primitive behavior. Heterogeneity of realworld entities is captured by allowing the user to give thebeings different biological characteristics (e.g. level ofintelligence and risk taking) using a control panel. Ourpaper focuses on our modifications and additions to thework inspired from the sugarscape problem [2].Interesting statistics are obtained from test-runs. TheMAS and the GUI that allows the user to control andobserve the model were developed using our Agent BaseEnvironment built on top of the Mozart ProgrammingSystem; a general-purpose development platform thatsupports concurrency, distribution, resource-aware andsymbolic computation. 1. Introduction In order to investigate the effect of the interplay ofvarious social parameters, social and behavioral scientistshave relied heavily on modeling. Traditional modelingapproaches have the disadvantage of suppressing theheterogeneity of real-world entities [2], deprivingscientists of the benefit of observing the effect ofindividual (microscopic) differences on the aggregate(macroscopic) behavior. The concept of “swarmintelligence” has been recently employed in various areaswhere centralization proved too inefficient or untenable.Each entity in the system aims at carrying out its ownplan and seeking its own good using its own simple rules.The collective plans of all entities culminate in theachievement of a globally sought goal that an individualparticipant does not have enough knowledge or resourcesto pursue. This concept was utilized in modeling complexsocial and behavioral phenomena, as well as in otherdomains, like economics and chemistry. Multi-agent Systems (MAS) [12] is one approach thathelps implementing the above concept since it allows alarge number of (possibly heterogeneous) agents to actautonomously and interact with each other to simulatereal-life entities. The need for large numbers of agents has laid certainguidelines for the implementation of a MAS simulation.The first of these is for an agent to be light-weight toallow the use of large numbers of agents without seriouslyaffecting system performance. Distribution allows agentsto reside on different hosts. Parallelisation techniquesbecome crucial to speed up simulation. MAS shouldtypically be fitted with a graphical tool that allowscontrolling as well as visually observing variousparameters and activities. Since the primary goal of aMAS is to enable modelers to draw conclusions from theirmodels, there should be a way of obtaining usefulinformation from data generated by the model. MAS canhave a statistical add-in that aggregates data to allowmodelers to investigate how/if some parameters correlate. In this paper, we present a MAS simulating individualsin a simple environment. The original scenario wasobtained from [2]; some formulae were then modified,various extensions to the model were proposed andparallel implementation techniques were employed.Agents representing various entities are shown at work ina community of “beings” that aim at maximizing theirwealth of food, and with this in mind, they can reasonabout a number of different activities. The following section presents our simulation modeland interesting statistical results from various runs," @default.
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• W128152812 date "2002-01-01" @default.
• W128152812 modified "2023-09-28" @default.
• W128152812 title "A Multi-Agent System for Behavioral Studies." @default.
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