We introduce a new language learning setting relevant to building adaptive natural
language interfaces. It is inspired by Wittgenstein's language games: a human wishes to …

The current mainstream approach to train natural language systems is to expose them to
large amounts of text. This passive learning is problematic if we are interested in developing …

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 …

We present a method for combining multi-agent communication and traditional data-driven
approaches to natural language learning, with an end goal of teaching agents to …

There is renewed interest in simulating language emergence among deep neural agents
that communicate to jointly solve a task, spurred by the practical aim to develop language …

Referential games offer a grounded learning environment for neural agents which accounts
for the fact that language is functionally used to communicate. However, they do not take into …

A hallmark of human intelligence is the ability to understand and communicate with
language. Interactive Fiction games are fully text-based simulation environments where a …

The principle of compositionality, which enables natural language to represent complex
concepts via a structured combination of simpler ones, allows us to convey an open-ended …

The ability of algorithms to evolve or learn (compositional) communication protocols has
traditionally been studied in the language evolution literature through the use of emergent …

In this work, we propose a computational framework in which agents equipped with
communication capabilities simultaneously play a series of referential games, where agents …