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MASON: A Multiagent Simulation Environment
MASON is a fast, easily extensible, discrete-event multi-agent simulation toolkit in Java, designed to serve as the basis for a wide range of multi-agent simulation tasks ranging from swarm roboticsExpand
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Cooperative Multi-Agent Learning: The State of the Art
Cooperative multi-agent systems (MAS) are ones in which several agents attempt, through their interaction, to jointly solve tasks or to maximize utility. Due to the interactions among the agents,Expand
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MASON: A New Multi-Agent Simulation Toolkit
We introduce MASON, a fast, easily extendable, discreteevent multi-agent simulation toolkit in Java. MASON was designed to serve as the basis for a wide range of multiagent simulation tasks rangingExpand
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MASON : A Multi-Agent Simulation Environment
We introduce MASON, a fast, easily extensible, discrete-event multi-agent simulation toolkit in Java. MASON was designed to serve as the basis for a wide range of multiagent simulation tasks rangingExpand
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Genetic programming needs better benchmarks
Genetic programming (GP) is not a field noted for the rigor of its benchmarking. Some of its benchmark problems are popular purely through historical contingency, and they can be criticized as tooExpand
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SHOE: A Knowledge Representation Language for Internet Applications
It is our contention that the World Wide Web poses challenges to knowledge representation systems that fundamentally change the way we should design KR languages. In this paper, we describe theExpand
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Ontology-based Web agents
This paper describes SHOE, a set of Simple HTML Ontology Extensions which allow World-Wide Web authors to annotate their pages with semantic knowledge such as “I am a graduate student” or “ThisExpand
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A Comparison of Bloat Control Methods for Genetic Programming
Genetic programming has highlighted the problem of bloat, the uncontrolled growth of the average size of an individual in the population. The most common approach to dealing with bloat in tree-basedExpand
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Evolving teamwork and coordination with genetic programming
Some problems can be solved only by multiagent teams. In using genetic programming to produce such teams, one faces several design decisions. First, there are questions of team diversity and ofExpand
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A pheromone-based utility model for collaborative foraging
  • Liviu Panait, S. Luke
  • Computer Science
  • Proceedings of the Third International Joint…
  • 19 July 2004
Multi-agent research often borrows from biology, where remarkable examples of collective intelligence may be found. One interesting example is ant colonies¿ use of pheromones as a joint communicationExpand
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