Group formation in large social networks: membership, growth, and evolution
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Analyzing characteristics of task structures to develop GPGP coordination mechanisms
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Managing complex scheduling problems with dynamic and hybrid constraints
Managing complex scheduling problems with dynamic and hybrid constraints
A team formation model based on knowledge and collaboration
Expert Systems with Applications: An International Journal
Finding a team of experts in social networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Evaluating hybrid constraint tightening for scheduling agents
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Human agent collaboration in a simulated combat medical scenario
CTS '09 Proceedings of the 2009 International Symposium on Collaborative Technologies and Systems
Hybrid constraint tightening for solving hybrid scheduling problems
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Forming effective worker teams with multi-functional skill requirements
Computers and Industrial Engineering - Special issue: Group technology/cellular manufacturing
TACAS'08/ETAPS'08 Proceedings of the Theory and practice of software, 14th international conference on Tools and algorithms for the construction and analysis of systems
From infrastructure delivery to service management in clouds
Future Generation Computer Systems
Editorial: Special Issue on Advances in Computer Supported Collaboration: Systems and Technologies
Future Generation Computer Systems
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Selecting and scheduling human experts to cooperatively solve a problem can be a highly complex task, given various constraints (such as what expertise is needed and when) and preferences (such as which expertise an expert most prefers to exercise). Computational agents can thus greatly help users form and schedule expert teams. This paper introduces a new formulation of the team formation and scheduling problem as a Hybrid Scheduling Problem (HSP) and compares the performance of an agent using the HSP formulation to a prior agent-based approach. We empirically demonstrate the promise of the HSP formulation and highlight how the application of HSP techniques to this problem has led us to identify important modifications to mechanisms that improve HSP solving. Finally, we summarize how the HSP formulation can support human-agent collaboration during the process of forming and scheduling expert teams.