Multi-Agent Pathfinding with Continuous TimeThis article has no associated abstract. ( fix it )Anton AndreychukKonstantin YakovlevPavel SurynekDor AtzmonRoni SternAndreychuk, A., Yakovlev, K., Atzmon, D., Stern, R.: Multi-agent pathfinding (MAPF) with continuous time. CoRR abs/1901.05506 (2019), http://arxiv.org/abs/1901.05506
Multi-agent pathfinding with continuous time Artificial Intelligence, 305 (2022) Google Scholar [20] H. Ma, W. Hönig, T. Kumar, N. Ayanian, S. Koenig, Lifelong path planning with kinematic constraints for multi-agent pickup and delivery, in: Proc. AAAI, 2019, pp. 7651–7658. Google ...
Andreychuk, A., Yakovlev, K., Atzmon, D., Stern, R.: Multi-agent pathfinding with continuous time. In: International Joint Conference on Artificial Intelligence (IJCAI), pp. 39–45 (2019) Google Scholar Atzmon, D., Stern, R., Felner, A., Wagner, G., Barták, R., Zhou, N.F.:...
Lillicrap TP, Hunt JJ, Pritzel A et al (2015) Continuous control with deep reinforcement learning. arXiv preprint arXiv:150902971 Lin T, Huh J, Stauffer C et al (2021) Learning to ground multi-agent communication with autoencoders. Adv Neural Inf Process Syst 34:15230–15242 Google Scholar...
MoveToBasket builds a path from the player’s position up to the basket; if the plan fails or becomes unfeasible, then that path is erased and recalculated again. The PathFinding algorithm is a search algorithm; in this case, an A* algorithm. Path finding algorithms are...
However, COMA can be easily extended to continuous actions spaces by estimating the expectation in (4) with Monte Carlo samples or using functional forms that render it analytical, e.g., Gaussian policies and critic. The following lemma establishes the convergence of COMA to a locally optimal ...
In the real world agents have a shape, and usually execute actions with variable duration. This thesis re-formulates the MAPF problem definition for continuous actions, designates specific techniques for continuous-time collision detection, re-formulates two popular algorithms for continuous actions and...
ESO-MAPF: Bridging Discrete Planning and Continuous Execution in Multi-Agent PathfindingWe present ESO-MAPF, a research and educational platform for experimenting with multi-agent path finding (MAPF). ESO-MAPF focuses on demonstrating the planning-acting chain in the MAPF domain. MAPF is the task ...
Lillicrap T, Hunt JJ, Pritzel A, Heess N, Erez T, Tassa Y, Silver D, Wierstra D (2016) Continuous control with deep reinforcement learning. In: ICLR (Poster) Lin K, Zhao R, Zhe X, Zhou J (2018) Efficient large-scale fleet management via multi-agent deep reinforcement learning. In...
Polynomial-Time Multi-Agent Pathfinding with Heterogeneous and Self-Interested Agents. In: Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, International Foundation for Autonomous Agents and Multiagent Systems, 2019;pp 2105–2107. 22. Morris R, Pasareanu CS,...