evoML Yellow Paper: Evolutionary AI and Optimisation Studio

no code implementations • 20 Dec 2022 • Lingbo Li, Leslie Kanthan, Michail Basios, Fan Wu, Manal Adham, Vitali Avagyan, Alexis Butler, Paul Brookes, Rafail Giavrimis, Buhong Liu, Chrystalla Pavlou, Matthew Truscott, Vardan Voskanyan

Additionally, a key feature of evoML is that it embeds code and model optimisation into the model development process, and includes multi-objective optimisation capabilities.

Navigate

Inducing Cooperation via Team Regret Minimization based Multi-Agent Deep Reinforcement Learning

no code implementations • 18 Nov 2019 • Runsheng Yu, Zhenyu Shi, Xinrun Wang, Rundong Wang, Buhong Liu, Xinwen Hou, Hanjiang Lai, Bo An

Existing value-factorized based Multi-Agent deep Reinforce-ment Learning (MARL) approaches are well-performing invarious multi-agent cooperative environment under thecen-tralized training and decentralized execution(CTDE) scheme, where all agents are trained together by the centralized valuenetwork and each agent execute its policy independently.

Deep Reinforcement Learning reinforcement-learning +1