Dynamic mode choice of commuters in an agent-based simulation model with inductive learning machines

Sunitiyoso, Yos and Matsumoto, Shoji (2005) Dynamic mode choice of commuters in an agent-based simulation model with inductive learning machines. Journal of Advanced Computational Intelligence and Intelligent Informatics, 9 (3), 329-336.

Abstract

This study applies an agent-based approach to modeling
a transport system. Using the advantage of agentbased
models of being validated at an individual level,
a social dilemma of travel mode choice is modeled and
viewed as a complex system. An inductive learning
machine is combined with an evolutionary approach
to simulate traveler learning. A user-equilibrium point
predicted by conventional analysis is reached and stabilized.

The stable situation is produced by interaction
among agents and by behavioral change of each agent,
without a central or external rule that organizes objectives of the system. The study shows conditions that
may produce other stable situations besides the user
equilibrium point. An emergent situation combined
with traveler sensitivity to payoff differences is influential.

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