Towards Situated Communication in Multi-Step Interactions: Time is a Key Pressure in Communication Emergence

Aleksandra Kalinowska, Elnaz Davoodi, Kory W. Mathewson, Todd D. Murphey, Patrick Pilarski

Research output: Contribution to conferencePaperpeer-review

2 Scopus citations

Abstract

Enabling efficient communication in artificial agents brings us closer to machines that can cooperate with each other and with human partners. Hand-engineered approaches have substantial limitations, leading to increased interest in methods for communication to emerge autonomously between artificial agents. Most of the research in the field explores unsituated communication in one-step referential tasks. The tasks are not temporally interactive and lack time pressures typically present in natural communication and language learning. In these settings, agents can successfully learn what to communicate but not when or whether to communicate. Here, we extend the literature by assessing emergence of communication between reinforcement learning agents in a temporally interactive, cooperative task of navigating a gridworld environment. We show that, through multi-step interactions, agents develop just-in-time messaging protocols that enable them to successfully solve the task. With memory-which provides flexibility around message timing-agent pairs converge to a look-ahead communication protocol, finding an optimal solution to the task more quickly than without memory. Lastly, we explore situated communication, enabling the acting agent to choose when and whether to communicate. With the opportunity cost of forgoing an action to communicate, the acting agent learns to solicit information sparingly, in line with the Gricean Maxim of quantity. Our results point towards the importance of studying language emergence through situated communication in multi-step interactions.

Original languageEnglish (US)
Pages615-620
Number of pages6
StatePublished - 2022
Event44th Annual Meeting of the Cognitive Science Society: Cognitive Diversity, CogSci 2022 - Toronto, Canada
Duration: Jul 27 2022Jul 30 2022

Conference

Conference44th Annual Meeting of the Cognitive Science Society: Cognitive Diversity, CogSci 2022
Country/TerritoryCanada
CityToronto
Period7/27/227/30/22

Keywords

  • artificial agents
  • cooperative game
  • emergent communication
  • reinforcement learning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Cognitive Neuroscience

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