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AAAI 2016

MIP-Nets: Enabling Information Sharing in Loosely-Coupled Teamwork

Conference Paper Papers Artificial Intelligence

Abstract

People collaborate in carrying out such complex activities as treating patients, co-authoring documents and developing software. While technologies such as Dropbox and Github enable groups to work in a distributed manner, coordinating team members’ individual activities poses significant challenges. In this paper, we formalize the problem of “information sharing in loosely-coupled extended-duration teamwork”. We develop a new representation, Mutual Influence Potential Networks (MIP-Nets), to model collaboration patterns and dependencies among activities, and an algorithm, MIP-DOI, that uses this representation to reason about information sharing.

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Context

Venue
AAAI Conference on Artificial Intelligence
Archive span
1980-2026
Indexed papers
28718
Paper id
458781362656434026