WebOverview: Any-Play Learning Augmentation for Zero-Shot Coordination. This library implements the Any-Play learning augmentation in Hanabi Learning Environment.Any-Play is an intrisictly-motivated, diversity-based augmentation for reinforcement learning algorithms (RL) that enables RL agents to effectively cooperate with novel, never-before-seen … WebMay 9, 2024 · We show that existing state-of-the-art cooperative AI algorithms, such as Other-Play and Off-Belief Learning, under-perform in this paradigm. We propose the Any-Play learning augmentation---a multi-agent extension of diversity-based intrinsic rewards for zero-shot coordination (ZSC)---for generalizing self-play-based algorithms to the inter …

"Other-Play" for Zero-Shot Coordination DeepAI

Web"Other-Play" for Zero-Shot Coordination . We consider the problem of zero-shot coordination - constructing AI agents that can coordinate with novel partners they have … http://www.crm.umontreal.ca/2024/Game21/pdf/Foerster1.pdf eotech magnifier lower 1/3

"Other-Play" for Zero-Shot Coordination – arXiv Vanity

WebJan 16, 2024 · Zero-shot human-AI coordination holds the promise of collaborating with humans without human data. Prevailing methods try to train the ego agent with a population of partners via self-play. WebOther-Play(Rank Bot) b. Other-Play(Color Bot) 4. Zero-Shot human-AI: a. Clone Bot from huma data. Analysis of Play-Style in Hanabi 40. Results in Hanabi 41. Summary I presented: Zero-shot coordination, a proxy setting for human-AI Off-Belief Learning, a novel method that allows agents to learn optimal WebThis setting is related, but zero-shot coordination gives no behavioral data to either agent to guide self-play or allow building a model of the other agent. Instead, zero-shot makes the … eotech light