Comparing two multiagent reinforcement learning approaches for the traffic assignment problem

R Grunitzki, ALC Bazzan - 2017 Brazilian Conference on …, 2017 - ieeexplore.ieee.org
The traffic assignment problem (TAP) consists of assigning routes to trips, in order to
minimize the travel time of all these trips. Classical methods assume the existence of a …

[PDF][PDF] Combining Car-to-Infrastructure Communication and Multi-Agent Reinforcement Learning in Route Choice.

R Grunitzki, ALC Bazzan - ATT@ IJCAI, 2016 - researchgate.net
Route choice is an important stage in transport planning and modeling. Most of the existing
approaches do not consider that road users can nowadays consult new technologies to plan …

A distributed assignment method for dynamic traffic assignment using heterogeneous-adviser based multi-agent reinforcement learning

Z Pan, Z Qu, Y Chen, H Li, X Wang - IEEE Access, 2020 - ieeexplore.ieee.org
The Dynamic Traffic Assignment (DTA) is one of the important measures to alleviate urban
network traffic congestion. The congestions are usually caused by stochastic traffic …

Travel package recommendation based on reinforcement learning and trip guaranteed prediction

JH Chang, HH Chiang, HX Zhong… - Journal of Internet …, 2021 - jit.ndhu.edu.tw
Trip planning research and travel package recommendation benefit from current trends in
Location Based Social Networks and trajectory related sites nowadays. Travel package …

Comprehensive Overview of Reward Engineering and Shaping in Advancing Reinforcement Learning Applications

S Ibrahim, M Mostafa, A Jnadi, P Osinenko - arXiv preprint arXiv …, 2024 - arxiv.org
The aim of Reinforcement Learning (RL) in real-world applications is to create systems
capable of making autonomous decisions by learning from their environment through trial …

[PDF][PDF] Dynamic Traffic Assignment and Routing Algorithms with Applications in Smart Mobility

DMF Rodrigues - 2023 - repositorio-aberto.up.pt
Transportation forecasting is the area concerned with analyzing, modeling, simulating and
validating mobility models for people in a constructed environment, typically in an urban …

Towards the user equilibrium in traffic assignment using GRASP with path relinking

GO Ramos, ALC Bazzan - Proceedings of the 2015 Annual Conference …, 2015 - dl.acm.org
Solving the traffic assignment problem (TAP) is an important step towards an efficient usage
of the traffic infrastructure. A fundamental assignment model is the so-called User …

Estudio de un algoritmo genetico para la administracion academica

AF Salazar, JF López, A Tavizón… - Formación …, 2019 - SciELO Chile
El presente trabajo de investigación tiene como objetivo ayudar a evaluar la conveniencia
del uso del método metaheurístico de algoritmos genéticos para la resolución de problemas …

Spatiotemporal AI for Transportation

T Cheng, J Haworth, MC Ozkan - Handbook of Geospatial Artificial …, 2023 - taylorfrancis.com
Spatiotemporal AI has played an important role in transportation research since the latter
part of the 20th century, predating the origin of the term as a way of describing AI based …

[图书][B] Distributed Optimization, Game and Learning Algorithms

H Wang, H Li, B Zhou - 2021 - Springer
Advances in wireless technology and computing power have necessitated the development
of theory, models, and tools to cope with the new challenges posed by large-scale control …