Zobrazeno 1 - 10
of 10 239
pro vyhledávání: '"cs.MA"'
Ride-pooling, to gain momentum, needs to be attractive for all the parties involved. This includes also drivers, who are naturally reluctant to serve pooled rides. This can be controlled by the platform's pricing strategy, which can stimulate drivers
Externí odkaz:
http://arxiv.org/abs/2403.13384
Publikováno v:
IEEE Robotics and Automation Letters. 8:3214-3221
We propose an extension to the MAPF formulation, called SocialMAPF, to account for private incentives of agents in constrained environments such as doorways, narrow hallways, and corridor intersections. SocialMAPF is able to, for instance, accurately
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8948f72b7d5903e3235d6863f30bb736
https://doi.org/10.1109/lra.2023.3265169
https://doi.org/10.1109/lra.2023.3265169
Autor:
Zhiquan Lai, Shengwei Li, Xudong Tang, Keshi Ge, Weijie Liu, Yabo Duan, Linbo Qiao, Dongsheng Li
Publikováno v:
IEEE Transactions on Parallel and Distributed Systems. 34:1466-1478
Foundation models are becoming the dominant deep learning technologies. Pretraining a foundation model is always time-consumed due to the large scale of both the model parameter and training dataset. Besides being computing-intensive, the training pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0a2ffcf75d20114e0b298d41511b1662
https://doi.org/10.1109/tpds.2023.3247001
https://doi.org/10.1109/tpds.2023.3247001
Publikováno v:
IEEE Transactions on Automatic Control. 68:2245-2260
We develop a probabilistic control algorithm, $\texttt{GTLProCo}$, for swarms of agents with heterogeneous dynamics and objectives, subject to high-level task specifications. The resulting algorithm not only achieves decentralized control of the swar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::851ff1d3ca9bb8f277bed526d66183e4
https://doi.org/10.1109/tac.2022.3176797
https://doi.org/10.1109/tac.2022.3176797
Publikováno v:
IEEE Transactions on Automation Science and Engineering. 20:789-804
Emerging vehicular systems with increasing proportions of automated components present opportunities for optimal control to mitigate congestion and increase efficiency. There has been a recent interest in applying deep reinforcement learning (DRL) to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13df1c2faa911b049e11311566ae881d
https://doi.org/10.1109/tase.2022.3168621
https://doi.org/10.1109/tase.2022.3168621
Autor:
Ameri E., Afshin, Miloradovic, Branko, Çürüklü, Baran, Papadopoulos, Alessandro, Ekström, Mikael, Dréo, Johann
Publikováno v:
IEEE International Conference on Systems, Man, and Cybernetics (SMC)
IEEE International Conference on Systems, Man, and Cybernetics (SMC), IEEE SMC Society, Oct 2023, Maui (Hawaii), United States
IEEE International Conference on Systems, Man, and Cybernetics (SMC), IEEE SMC Society, Oct 2023, Maui (Hawaii), United States
International audience; With the rapidly growing use of Multi-Agent Systems (MASs), which can exponentially increase the system complexity, the problem of planning a mission for MASs became more intricate. In some MASs, human operators are still invo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2100::71fd5bb89063cef7ed8fdc10c4b39fa7
https://hal.science/hal-04116806/document
https://hal.science/hal-04116806/document
Publikováno v:
Electronic Proceedings in Theoretical Computer Science. 361:61-77
A swarm robotic system consists of a team of robots performing cooperative tasks without any centralized coordination. In principle, swarms enable flexible and scalable solutions; however, designing individual control algorithms that can guarantee a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c6979eace4a295d5025533c612284b9
https://doi.org/10.4204/eptcs.361.7
https://doi.org/10.4204/eptcs.361.7
Autor:
Hossein Moradian, Solmaz S. Kia
Publikováno v:
IEEE Transactions on Control of Network Systems. 10:157-168
In this paper, we study accelerating a Laplacian-based dynamic average consensus algorithm by splitting the conventional delay-free disagreement feedback into weighted summation of a current and an outdated term. We determine for what weighted sum th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98e9e11e9f43a428f53c0075676430bd
https://doi.org/10.1109/tcns.2022.3188481
https://doi.org/10.1109/tcns.2022.3188481
Publikováno v:
Proceedings of the ACM on Measurement and Analysis of Computing Systems. 7:1-51
We study a multi-agent reinforcement learning (MARL) problem where the agents interact over a given network. The goal of the agents is to cooperatively maximize the average of their entropy-regularized long-term rewards. To overcome the curse of dime
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::47fbb8865a9ed33fb554bee836cca7df
https://doi.org/10.1145/3579443
https://doi.org/10.1145/3579443
Publikováno v:
SIAM Journal on Optimization. 33:294-318
We present the concept of a Generalized Feedback Nash Equilibrium (GFNE) in dynamic games, extending the Feedback Nash Equilibrium concept to games in which players are subject to state and input constraints. We formalize necessary and sufficient con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::88fdd052a799a9f1928c1e03c0f5f13a
https://doi.org/10.1137/21m142530x
https://doi.org/10.1137/21m142530x