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Multi-Agent Organizer

Multi-Agent Organizer. by Kogan Tanya Shusterman Evgeny. Advisor : Domshlak Carmel. Motivation. Solve the problem of meeting scheduling between two persons. Schedule a meeting and satisfy user ’ s individual preferences. Keep user ’ s calendar and preferences information private.

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Multi-Agent Organizer

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  1. Multi-Agent Organizer by Kogan Tanya Shusterman Evgeny Advisor: Domshlak Carmel

  2. Motivation • Solve the problem of meeting scheduling between two persons. • Schedule a meeting and satisfy user’s individual preferences. • Keep user’s calendar and preferences information private.

  3. Basic Definitions • Agent - software module that negotiate and schedules meetings. • User - person that owns the agent. • Preferences on the values of various meeting parameters. • Constraints on the meeting parameters which either explicitly specified by the user or derived from the current state of the schedule.

  4. Project Parts • Negotiation algorithm between the agents. • Finding preferentially Pareto-optimal solution for current meeting proposal. • Convenient graphic user interface.

  5. CP-network (Boutilier et al. 99`) An intuitive, qualitative, graphical model of preferences, that captures statements of conditional preferential independence. • DAG in which each node represent a state variable. • The immediate parents of a variable in the network are those variables that affect user’s preference over its values. • Any CP-network defines a consistent partial order over the complete assignments on its variables.

  6. A B C D E F Example of a CP-network

  7. My preferences: If I have “Presentation” then I’d like to do it during the morning or at 12:00. If I have a meeting with Jon during the morning then I prefer to do it in Haifa, otherwise I prefer to do it in Beer-Sheva. Translation for software (this) "subject" "Presentation" -> (this) "time" morning 12:00 (person) “Jon" 1 & (time) "morning" 1 -> (this) "place" Tel-Aviv Haifa (person) “Jon" 1 & (time) "morning" 0 -> (this) "place" Beer-Sheva. Preferences definition

  8. CP-network with constraint arcs subject Jon time place town constraints length day preferences

  9. Main window

  10. User’s Request for Meeting

  11. Negotiation Algorithm Agent A Agent B Meeting request generate request generate all offers Send first offer generate offer check constraints No generate offer Send next offer generate offer insert meeting Yes insert meeting

  12. Finding Solutions Given a CP-network and the current constraints, generate a list of all feasible offers for a meeting, sorted according to the preferences of the user. This generator is based on the algorithm for constraint-based preferential optimization from [2].

  13. Viewing of results

  14. Confirmation Owner Agent Request for new meetings extract new meeting Show new meeting Confirm Reject enter the meeting into the dairy start negotiation from begining

  15. Tools • Python 2.0 for Windows • Java • Gadfly (database support) • IMAP4 (mail protocol)

  16. Future development • Providing an approach for scheduling meetings with more than two agents. • Development of more natural language for preference and constrains elicitation.

  17. Bibliography • Craig Boultilier, Ronen I Brafman, Holger H. Hoos and David Pool. Reasoning with Conditional Ceteris Paribus Preference Statements (1999) • Craig Boultilier, Ronen I Brafman, Chris Geib and David Poole. A Constraint-Based Approach to Preference Elicitation and Decision Making (1997). • Sandip Sen. An automated distributed meeting scheduler. (Department of Mathematical & Computer Sciences, University of Tulsa) • Leonardo Garrido, Katia Sycara. Multi-Agent Meeting Scheduling: Preliminary Experimental Results. • Axel van Lamsweerde, Robert Darimont and Philipe Massonet. The Meeting Scheduler System - Problem Statement. (University Catholique de Louvain, Belgium)

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