Authors
Benjamin Kolb
Leon Lang
Henning Bartsch
Arwin Gansekoele
Raymond Koopmanschap
Leonardo Romor
David Speck
Mathijs Mul
Elia Bruni
Date (dd-mm-yyyy)
2019
Title
Learning to request guidance in emergent communication
Publication Year
2019
Number of pages
10
Publisher
Association for Computational Linguistics
Document type
Conference contribution
Abstract

Previous research into agent communication has shown that a pre-trained guide can speed up the learning process of an imitation learning agent. The guide achieves this by providing the agent with discrete messages in an emerged language about how to solve the task. We extend this one-directional communication by a one-bit communication channel from the learner back to the guide: It is able to ask the guide for help, and we limit the guidance by penalizing the learner for these requests. During training, the agent learns to control this gate based on its current observation. We find that the amount of requested guidance decreases over time and guidance is requested in situations of high uncertainty. We investigate the agent's performance in cases of open and closed gates and discuss potential motives for the observed gating behavior.

URL
go to publisher's site
Permalink
https://hdl.handle.net/11245.1/1e4faae2-a9e4-4f20-a05f-97c80869d298
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