A Unified Decision-Theoretic Model for Information Gathering and Communication Planning

Conference paper (2020)

Authors

Jennifer Renoux Örebro University
Tiago S. Veiga University of Lisbon, Norwegian University of Science and Technology (NTNU)
Pedro U. Lima University of Lisbon
M.T.J. Spaan Algorithmics - EEMCS
Research Group
Algorithmics (EEMCS) (TU Delft)
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Published Date

2020

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Software Technology

Research Group

Algorithmics

Abstract

We consider the problem of communication planning for human-machine cooperation in stochastic and partially observable environments. Partially Observable Markov Decision Processes with Information Rewards (POMDPs-IR) form a powerful framework for information-gathering tasks in such environments. We propose an extension of the POMDP-IR model, called a Communicating POMDP-IR (com-POMDP-IR), that allows an agent to proactively plan its communication actions by using an approximation of the human’s beliefs. We experimentally demonstrate the capability of our com-POMDPIR agent to limit its communication to relevant information and its robustness to lost messages.

Files

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