Emergent multi-agent communication in the deep learning era
A Lazaridou, M Baroni - arXiv preprint arXiv:2006.02419, 2020 - arxiv.org
The ability to cooperate through language is a defining feature of humans. As the
perceptual, motory and planning capabilities of deep artificial networks increase …
perceptual, motory and planning capabilities of deep artificial networks increase …
Human-level play in the game of Diplomacy by combining language models with strategic reasoning
Meta Fundamental AI Research Diplomacy Team … - Science, 2022 - science.org
Despite much progress in training artificial intelligence (AI) systems to imitate human
language, building agents that use language to communicate intentionally with humans in …
language, building agents that use language to communicate intentionally with humans in …
The rise and potential of large language model based agents: A survey
For a long time, humanity has pursued artificial intelligence (AI) equivalent to or surpassing
the human level, with AI agents considered a promising vehicle for this pursuit. AI agents are …
the human level, with AI agents considered a promising vehicle for this pursuit. AI agents are …
A survey on reinforcement learning methods in character animation
Reinforcement Learning is an area of Machine Learning focused on how agents can be
trained to make sequential decisions, and achieve a particular goal within an arbitrary …
trained to make sequential decisions, and achieve a particular goal within an arbitrary …
Language instructed reinforcement learning for human-ai coordination
One of the fundamental quests of AI is to produce agents that coordinate well with humans.
This problem is challenging, especially in domains that lack high quality human behavioral …
This problem is challenging, especially in domains that lack high quality human behavioral …
Collaborating with humans without human data
Collaborating with humans requires rapidly adapting to their individual strengths,
weaknesses, and preferences. Unfortunately, most standard multi-agent reinforcement …
weaknesses, and preferences. Unfortunately, most standard multi-agent reinforcement …
Imitating human behaviour with diffusion models
Diffusion models have emerged as powerful generative models in the text-to-image domain.
This paper studies their application as observation-to-action models for imitating human …
This paper studies their application as observation-to-action models for imitating human …
Open problems in cooperative ai
Problems of cooperation--in which agents seek ways to jointly improve their welfare--are
ubiquitous and important. They can be found at scales ranging from our daily routines--such …
ubiquitous and important. They can be found at scales ranging from our daily routines--such …
Simulation intelligence: Towards a new generation of scientific methods
The original" Seven Motifs" set forth a roadmap of essential methods for the field of scientific
computing, where a motif is an algorithmic method that captures a pattern of computation …
computing, where a motif is an algorithmic method that captures a pattern of computation …
“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 not seen before (eg humans). Standard Multi …
coordinate with novel partners they have not seen before (eg humans). Standard Multi …