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To Adapt or Not to Adapt – Consequences of Adapting Driver and Traffic Light Agents

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Adaptive Agents and Multi-Agent Systems III. Adaptation and Multi-Agent Learning (AAMAS 2005, ALAMAS 2007, ALAMAS 2006)

Abstract

One way to cope with the increasing traffic demand is to integrate standard solutions with more intelligent control measures. However, the result of possible interferences between intelligent control or information provision tools and other components of the overall traffic system is not easily predictable. This paper discusses the effects of integrating co-adaptive decision-making regarding route choices (by drivers) and control measures (by traffic lights). The motivation behind this is that optimization of traffic light control is starting to be integrated with navigation support for drivers. We use microscopic, agent-based modelling and simulation, in opposition to the classical network analysis, as this work focuses on the effect of local adaptation. In a scenario that exhibits features comparable to real-world networks, we evaluate different types of adaptation by drivers and by traffic lights, based on local perceptions. In order to compare the performance, we have also used a global level optimization method based on genetic algorithms.

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Karl Tuyls Ann Nowe Zahia Guessoum Daniel Kudenko

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Bazzan, A.L.C., de Oliveira, D., Klügl, F., Nagel, K. (2008). To Adapt or Not to Adapt – Consequences of Adapting Driver and Traffic Light Agents. In: Tuyls, K., Nowe, A., Guessoum, Z., Kudenko, D. (eds) Adaptive Agents and Multi-Agent Systems III. Adaptation and Multi-Agent Learning. AAMAS ALAMAS ALAMAS 2005 2007 2006. Lecture Notes in Computer Science(), vol 4865. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77949-0_1

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  • DOI: https://doi.org/10.1007/978-3-540-77949-0_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-77947-6

  • Online ISBN: 978-3-540-77949-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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