AIMADec 15, 2020

Open Problems in Cooperative AI

arXiv:2012.08630v1262 citations
AI Analysis

This paper proposes a new research direction for the AI community, aiming to address the fundamental problem of cooperation for both AI agents and human-AI systems, which is foundational for many real-world challenges.

This paper identifies and defines 'Cooperative AI' as a new field of study, focusing on equipping AI agents with cooperation capabilities and developing tools to foster cooperation in mixed human-AI populations. It aims to integrate existing work from multi-agent systems, game theory, human-machine interaction, and natural language processing to address ubiquitous cooperation problems.

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 as driving on highways, scheduling meetings, and working collaboratively--to our global challenges--such as peace, commerce, and pandemic preparedness. Arguably, the success of the human species is rooted in our ability to cooperate. Since machines powered by artificial intelligence are playing an ever greater role in our lives, it will be important to equip them with the capabilities necessary to cooperate and to foster cooperation. We see an opportunity for the field of artificial intelligence to explicitly focus effort on this class of problems, which we term Cooperative AI. The objective of this research would be to study the many aspects of the problems of cooperation and to innovate in AI to contribute to solving these problems. Central goals include building machine agents with the capabilities needed for cooperation, building tools to foster cooperation in populations of (machine and/or human) agents, and otherwise conducting AI research for insight relevant to problems of cooperation. This research integrates ongoing work on multi-agent systems, game theory and social choice, human-machine interaction and alignment, natural-language processing, and the construction of social tools and platforms. However, Cooperative AI is not the union of these existing areas, but rather an independent bet about the productivity of specific kinds of conversations that involve these and other areas. We see opportunity to more explicitly focus on the problem of cooperation, to construct unified theory and vocabulary, and to build bridges with adjacent communities working on cooperation, including in the natural, social, and behavioural sciences.

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