Efficient ridesharing dispatch using multi-agent reinforcement learning
O De Lima, H Shah, TS Chu, B Fogelson - arXiv preprint arXiv:2006.10897, 2020 - arxiv.org
With the advent of ride-sharing services, there is a huge increase in the number of people
who rely on them for various needs. Most of the earlier approaches tackling this issue …
who rely on them for various needs. Most of the earlier approaches tackling this issue …
Deeppool: Distributed model-free algorithm for ride-sharing using deep reinforcement learning
AO Al-Abbasi, A Ghosh… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The success of modern ride-sharing platforms crucially depends on the profit of the ride-
sharing fleet operating companies, and how efficiently the resources are managed. Further …
sharing fleet operating companies, and how efficiently the resources are managed. Further …
AdaPool: An adaptive model-free ride-sharing approach for dispatching using deep reinforcement learning
M Haliem, V Aggarwal, B Bhargava - Proceedings of the 7th ACM …, 2020 - dl.acm.org
Deep Reinforcement Learning (RL) suffer from catastrophic forgetting due to being agnostic
to the timescale of changes in the distribution of experiences. Although, RL algorithms are …
to the timescale of changes in the distribution of experiences. Although, RL algorithms are …
[PDF][PDF] Deep reinforcement learning for ride-sharing dispatching and repositioning
In this demo, we will present a simulation-based human-computer interaction of deep
reinforcement learning in action on order dispatching and driver repositioning for ride …
reinforcement learning in action on order dispatching and driver repositioning for ride …
Mutual Information as Intrinsic Reward of Reinforcement Learning Agents for On-demand Ride Pooling
The emergence of on-demand ride pooling services allows each vehicle to serve multiple
passengers at a time, thus increasing drivers' income and enabling passengers to travel at …
passengers at a time, thus increasing drivers' income and enabling passengers to travel at …
An order dispatch system based on reinforcement learning for ride sharing services
Z Chen, P Li, J Xiao, L Nie, Y Liu - 2020 IEEE 22nd International …, 2020 - ieeexplore.ieee.org
Ride-sharing has been widely used in many cities, such as Didi and Uber. Ride-sharing is
regarded as an effective way to solve urban traffic congestion and pollution. However, most …
regarded as an effective way to solve urban traffic congestion and pollution. However, most …
A distributed model-free algorithm for multi-hop ride-sharing using deep reinforcement learning
A Singh, AO Al-Abbasi… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The growth of autonomous vehicles, ridesharing systems, and self-driving technology will
bring a shift in the way ride hailing platforms plan out their services. However, these …
bring a shift in the way ride hailing platforms plan out their services. However, these …
Efficient ridesharing order dispatching with mean field multi-agent reinforcement learning
A fundamental question in any peer-to-peer ridesharing system is how to, both effectively
and efficiently, dispatch user's ride requests to the right driver in real time. Traditional rule …
and efficiently, dispatch user's ride requests to the right driver in real time. Traditional rule …
A distributed model-free ride-sharing approach for joint matching, pricing, and dispatching using deep reinforcement learning
M Haliem, G Mani, V Aggarwal… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Significant development of ride-sharing services presents a plethora of opportunities to
transform urban mobility by providing personalized and convenient transportation while …
transform urban mobility by providing personalized and convenient transportation while …
A deep value-network based approach for multi-driver order dispatching
Recent works on ride-sharing order dispatching have highlighted the importance of taking
into account both the spatial and temporal dynamics in the dispatching process for …
into account both the spatial and temporal dynamics in the dispatching process for …