Roma Patel, Google DeepMind

Abstract

Insights from human language, for example, how compositional operators work over reusable concepts or how people communicate with one another to solve tasks, provide a rich source of information as to how intelligent behaviour arises in human beings. Can this help us endow agents with the ability to intelligently function in multi-agent populations in the same way that language-speaking humans do? In this talk we’ll go over several pieces of work in which language has been used to guide multi-agent decision making, as well as how insights from game theory can be used to build better language models. These recent works provide a preview of the future of research at the intersection of game theory and natural language processing, and the role that foundation models can play in this area.

[Video]