Emergence of Grounded Compositional Language in Multi-Agent Populations

Understand

By capturing statistical patterns in large corpora, machine learning has enabled significant advances in natural language processing, including in machine translation, question answering, and sentiment analysis.

• However, for agents to intelligently interact with humans, simply capturing the statistical patterns is insufficient.
• In this paper we investigate if, and how, grounded compositional language can emerge as a means to achieve goals in multi-agent populations.
• Towards this end, we propose a multi-agent learning environment and learning methods that bring about emergence of a basic compositional language.