Effects of Learning to Interact on the Evolution of
Social Behavior of Agents in Continuous Predators-prey
Pursuit Problem
Proceedings of the 7th European Conference on
Artificial Life (ECAL 2003), (2003)Abstract
the effect of learning to interact on the evolution of
social behaviour of agents situated in inherently
cooperative environment. Using continuous
predators-prey pursuit problem we verified our
hypothesis that relatively complex social behaviour may
emerge from simple, implicit, locally defined, and
therefore robust and highly-scalable interactions
between the predator agents. We argue that the ability
of agents to learn to perform simple, atomic acts of
implicit interaction facilitates the performance of
evolution of more complex, social behaviour. The
empirical results show about two-fold decrease of
computational effort of proposed strongly typed genetic
programming (STGP), used as an algorithmic paradigm to
evolve the social behavior of the agents, when STGP is
combined with learning of agents to implicitly interact
with each other.
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