AAAI 2016
MIP-Nets: Enabling Information Sharing in Loosely-Coupled Teamwork
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