Why CSCW applications fail: problems in the design and evaluationof organizational interfaces
CSCW '88 Proceedings of the 1988 ACM conference on Computer-supported cooperative work
Groupware and social dynamics: eight challenges for developers
Communications of the ACM
Experience with a learning personal assistant
Communications of the ACM
Meet your destiny: a non-manipulable meeting scheduler
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Satisfying user preferences while negotiating meetings
International Journal of Human-Computer Studies - Special issue: group support systems
Mixed-Initiative Issues in an Agent-Based Meeting Scheduler
User Modeling and User-Adapted Interaction
Learning User Evaluation Functions for Adaptive Scheduling Assistance
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Agent-Based Approach to Dynamic Meeting Scheduling Problems
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
Active preference learning for personalized calendar scheduling assistance
Proceedings of the 10th international conference on Intelligent user interfaces
Learning to select negotiation strategies in multi-agent meeting scheduling
EPIA'05 Proceedings of the 12th Portuguese conference on Progress in Artificial Intelligence
Learning user preferences in distributed calendar scheduling
PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling
Knowledge discovery for adaptive negotiation agents in e-marketplaces
Decision Support Systems
Optimal Choice and Beliefs with Ex Ante Savoring and Ex Post Disappointment
Management Science
Argumentation-based negotiation planning for autonomous agents
Decision Support Systems
Automatic Service Agreement Negotiators in Open Commerce Environments
International Journal of Electronic Commerce
On the engineering of agent-based simulations of social activities with social networks
Information and Software Technology
A bargaining-specific architecture for supporting automated service agreement negotiation systems
Science of Computer Programming
A set-based approach to negotiation with concessions
Proceedings of the Fifth Balkan Conference in Informatics
An Agent Based Approach to Patient Scheduling Using Experience Based Learning
International Journal of Agent Technologies and Systems
The Effects of Different Interaction Protocols in Agent-Based Simulation of Social Activities
International Journal of Agent Technologies and Systems
TESLA: an energy-saving agent that leverages schedule flexibility
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Towards a centralised appointments system to optimise the length of patient stay
Decision Support Systems
TESLA: an extended study of an energy-saving agent that leverages schedule flexibility
Autonomous Agents and Multi-Agent Systems
Agent-Based System Design for Service Process Scheduling: Challenges, Approaches and Opportunities
Journal of Integrated Design & Process Science
A personal meeting scheduling agent
Personal and Ubiquitous Computing
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This work presents a set of protocols for scheduling a meeting among agents that represent their respective user's interests. Four protocols are discussed: a) the full information protocol when all agents are comfortable with sharing their preference profile and free times; b) the approval protocol when only the preference profile can be shared; c) the voting protocol when only free time can be shared; and d) the suggestion protocol if neither preference nor free time can be shared. We use non-standard metric to evaluate the protocols which aims at maximizing the average preference, but also seeks to reduce the differences in preferences among the agents. The full information and approval protocols are optimal, that is, they achieve the best solution. Results show that the voting protocol achieves the best solution 88% of the time. Simulation results for the suggestion protocol with different numbers of agents, different numbers of solutions, and different strategies are presented. The suggestion protocol is shown to be coalition-free.