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Gama: Graph attention multi-agent reinforcement learning algorithm for cooperation
H Chen, Y Liu, Z Zhou, D Hu, M Zhang - Applied Intelligence, 2020 - Springer
Multi-agent reinforcement learning (MARL) is an important way to realize multi-agent
cooperation. But there are still many challenges, including the scalability and the uncertainty …
cooperation. But there are still many challenges, including the scalability and the uncertainty …
[PDF][PDF] Factor Graph Neural Network Meets Max-Sum: A Real-Time Route Planning Algorithm for Massive-Scale Trips
Global route planning (GRP) is a typical combinatorial optimization problem that has been
solved for a variety of industrial purposes, such as traffic flow management, network routing …
solved for a variety of industrial purposes, such as traffic flow management, network routing …
Multiagent decision making and learning in urban environments
A Kumar - 2019 - ink.library.smu.edu.sg
Our increasingly interconnected urban environments provide several opportunities to deploy
intelligent agents—from self-driving cars, ships to aerial drones—that promise to radically …
intelligent agents—from self-driving cars, ships to aerial drones—that promise to radically …
[PDF][PDF] Multiagent decision making and learning in urban environments.(2019)
A KUMAR - Proceedings of the 28th International Joint Conference … - core.ac.uk
Our increasingly interconnected urban environments provide several opportunities to deploy
intelligent agents—from self-driving cars, ships to aerial drones—that promise to radically …
intelligent agents—from self-driving cars, ships to aerial drones—that promise to radically …
チーム戦略シミュレーションゲームにおける自律キャラクタの協調攻撃機構の試作
間宮大夢， 福田直樹 - 第 82 回全国大会講演論文集, 2020 - ipsj.ixsq.nii.ac.jp
本研究における, チーム戦略シミュレーションゲームは, 複数の敵と敵の数よりも少ない自律
キャラクタが相手を倒していき, どちらかのチームの全員倒れるまで続けられるシミュレーション …
キャラクタが相手を倒していき, どちらかのチームの全員倒れるまで続けられるシミュレーション …