Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols

Understand

Learning to communicate through interaction, rather than relying on explicit supervision, is often considered a prerequisite for developing a general AI.

• We study a setting where two agents engage in playing a referential game and, from scratch, develop a communication protocol necessary to succeed in this game.
• Unlike previous work, we require that messages they exchange, both at train and test time, are in the form of a language (i.e.
• sequences of discrete symbols).