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Journal Articles International Journal of Ambient Computing and Intelligence Year : 2022

A Reinforcement Learning Integrating Distributed Caches for Contextual Road Navigation

Jean-Michel Ilié
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Ahmed-Chawki Chaouche

Abstract

Due to contextual traffic conditions, the computation of optimized or shortest paths is a very complex problem for both drivers and autonomous vehicles. This paper introduces a reinforcement learning mechanism that is able to efficiently evaluate path durations based on an abstraction of the available traffic information. The authors demonstrate that a cache data structure allows a permanent access to the results whereas a lazy politics taking new data into account is used to increase the viability of those results. As a client of the proposed learning system, the authors consider a contextual path planning application and they show in addition the benefit of integrating a client cache at this level. Our measures highlight the performance of each mechanism, according to different learning and caching strategies.
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Dates and versions

hal-03938697 , version 1 (13-01-2023)

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Jean-Michel Ilié, Ahmed-Chawki Chaouche, François Pêcheux. A Reinforcement Learning Integrating Distributed Caches for Contextual Road Navigation. International Journal of Ambient Computing and Intelligence, 2022, 13 (1), pp.1-19. ⟨10.4018/IJACI.300792⟩. ⟨hal-03938697⟩
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