Monte Carlo Tree Search Algorithm for SSPs Under the GUBS Criterion

Autor: Gabriel Nunes Crispino, Valdinei Freire, Karina Valdivia Delgado

Publikováno v: CLEI Electronic Journal, Vol 27, Iss 3 (2024)

The Stochastic Shortest Path (SSP) is a formalism widely used for modeling goal-oriented probabilistic planning problems. When dead ends, which are states from which goal states cannot be reached, are present in the problem and cannot be avoided, the

Externí odkaz: https://doaj.org/article/338c82f1e9ce4652bfb3e38c26b84ad5

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Reinforcement Learning Based Stochastic Shortest Path Finding in Wireless Sensor Networks

Autor: Wenwen Xia, Chong Di, Haonan Guo, Shenghong Li

Publikováno v: IEEE Access, Vol 7, Pp 157807-157817 (2019)

Many factors influence the connection states between nodes of wireless sensor networks, such as physical distance, and the network load, making the network's edge length dynamic in abundant scenarios. This dynamic property makes the network essential

Externí odkaz: https://doaj.org/article/8273418c69854c00a09e22ba6953b29d

Minimum costs paths in intermodal transportation networks with stochastic travel times and overbookings

Autor: Bernard G. Zweers, Rob van der Mei

Publikováno v: European Journal of Operational Research, 300(1), 178-188. Elsevier
European Journal of Operational Research, 300, 178-188
Zweers, B G & van der Mei, R D 2022, ' Minimum costs paths in intermodal transportation networks with stochastic travel times and overbookings ', European Journal of Operational Research, vol. 300, no. 1, pp. 178-188 . https://doi.org/10.1016/j.ejor.2021.07.042

In intermodal transportation, it is essential to balance the trade-off between the cost and duration of a route. The duration of a path is inherently stochastic because of delays and the possibility of overbooking. We study a problem faced by a compa

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::93e5bc6524e65e5755baea251923cef7
https://doi.org/10.1016/j.ejor.2021.07.042