Planning large systems with MDPs: case study of inland waterways supervision - Archive ouverte HAL
Article Dans Une Revue ADCAIJ: ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL Année : 2016

Planning large systems with MDPs: case study of inland waterways supervision

Guillaume Lozenguez
Arnaud Doniec
Éric Duviella

Résumé

Inland waterway management is likely to go through heavy changes due to an expected traffic increase in a context of climate change. Those changes will require an adaptive and resilient management of the water resource. The aim is to have an optimal plan for the distribution of the water resource on the whole inland waterway network, while taking into account the uncertainties arising from the operations of such a network. A representative model using Markov decision processes is proposed to model the dynamic and the uncertainties of the waterways. The proposed model is able to coordinate multiple entities over multiple time steps in order to prevent an overflow of a test network. However, this model suffers from a lack of scalability and is unable to represent real case applications. Advantages and limitations of several approaches of the literature to circumvent this limitation are discussed according to our case study.
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Dates et versions

hal-01577221 , version 1 (31-01-2024)

Identifiants

Citer

Guillaume Desquesnes, Guillaume Lozenguez, Arnaud Doniec, Éric Duviella. Planning large systems with MDPs: case study of inland waterways supervision. ADCAIJ: ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL, 2016, 5 (4), pp.71-84. ⟨10.14201/ADCAIJ2016547184⟩. ⟨hal-01577221⟩
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