• Publications
  • Influence
MASON: A Multiagent Simulation Environment
TLDR
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 multiagent simulation tasks ranging from swarm robotics to machine learning. Expand
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Cooperative Multi-Agent Learning: The State of the Art
TLDR
Cooperative multi-agent systems (MAS) are ones in which several agents attempt, through their interaction, to jointly solve tasks or maximize utility. Expand
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MASON: A New Multi-Agent Simulation Toolkit
TLDR
We introduce MASON, a fast, easily extendable, discreteevent multi-agent simulation toolkit in Java, designed to be flexible enough to be used for a wide range of simulations. Expand
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MASON : A Multi-Agent Simulation Environment
TLDR
We introduce MASON, a fast, easily extensible, discrete-event multi-agent simulation toolkit in Java, designed to be flexible enough to be used for a wide range of simple simulations. Expand
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Genetic programming needs better benchmarks
TLDR
Genetic programming (GP) is not a field noted for the rigor of its benchmarking. Expand
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SHOE: A Knowledge Representation Language for Internet Applications
TLDR
We describe the Simple HTML Ontology Extensions (SHOE), a KR language which allows web pages to be annotated with semantics. Expand
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A Comparison of Bloat Control Methods for Genetic Programming
TLDR
We examine several approaches to bloat control and report on their success in managing population size while retaining reasonable best-fitness-of run results. Expand
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Ontology-based Web agents
TLDR
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 “This person is my graduate advisor”. Expand
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Evolving teamwork and coordination with genetic programming
TLDR
We examine three breeding strategies (clones, free, and restricted) and three coordination mechanisms (none, deictic sensing, and name-based sensing) for evolving teams of agents in the Serengeti world, a simple predator/prey environment. Expand
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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
TLDR
We propose two pheromone-based algorithms for artificial agent foraging, trail-creation, and other tasks. Expand
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