Genetic Programming(GP) is a technique that can be used to automatically program computers
to perform some required task. The technique is a kind of genetic algorithm in which the representation
is a program parse tree instead of a bit-string and the fitness of each parse trees is
evaluated by executing the computer program that it represents.
The subject of this thesis is to investigate the use of GP to automatically program multiagent
systems. To achieve this goal, we consider the general problems in creating multiagent systems,
and show how GP can be used to provide solutions to many of them. Our key contributions are
as follows:
We show that it possible to evolve multi-agent systems using GP that:
exhibit coordinated, coherent behaviour
communicate explicitly, and in doing so decide what to communicate and how
can resolve conflicts
can be integrated into an existing society of agents
We also consider the scalability problems involved in the use of GP, both generally and in particular
as a technique for automatically programming agents, and propose solutions to these
problems.
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