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This report outlines the use of a relational representation in a Multi-Agent domain to model the behaviour of the whole system. A desired property in this systems is the ability of...
: The complexity and scope of software systems continues to grow. One approach to dealing with this growing complexity is the use of intelligent, multi-agent systems. However, due ...
Today's society is largely connected and many real life applications lend themselves to be modeled as multi-agent systems. Although such systems as well as their models are d...
The explosive growth in genomic (and soon, expression and proteomic) data, exemplified by the Human Genome Project, is a fertile domain for the application of multi-agent informat...
Keith Decker, Salim Khan, Carl Schmidt, Gang Situ,...
We analyze a general model of multi-agent communication in which all agents communicate simultaneously to a message board. A genetic algorithm is used to evolve multi-agent languag...
This paper describes the development of a distributed multi-agent workflow enacting mechanism starting from a BPEL4WS[BPE03] specification. Our work demonstrates that a multi-agent...
Learning Automata (LA) were recently shown to be valuable tools for designing Multi-Agent Reinforcement Learning algorithms. One of the principal contributions of LA theory is tha...
Cooperative multi-agent systems are ones in which several agents attempt, through their interaction, to jointly solve tasks or to maximize utility. Due to the interactions among t...
Abstract. This paper presents a multi-agent approach to gene expression analysis and illustrates the working steps using real dataset produced from a microarray experiment. The ana...
H. C. Lam, M. Vazquez, B. Juneja, Scott C. Fahrenk...
Multi-agent systems allow the simulation of complex phenomena that cannot easily be described analytically. Multi-agent approaches are often based on coordinating agents whose act...