1. 1RADAR – Scheduling Task © 2003 Carnegie Mellon University RADAR – Scheduling Task May 20, 2003 Manuela Veloso, Stephen Smith, Jaime Carbonell, Brett Browning, (Jay Modi, Eugene Fink)

2. 2RADAR – Scheduling Task © 2003 Carnegie Mellon University The Challenge Main Functions -- Calendar Management »Respond to meeting requests (extracted from ongoing email stream) »Initiate meetings requests and establish meetings »Continuously acquire user preferences and negotiation profiles Why not yet available »Requires capture and use of complex, ill-structured user preferences »Continuous scheduling »Management of rich multi-threaded information exchange under conflicting constraints and preferences Why now »Explore collaborative, user + EPCA, scheduling »Build upon integration of many leading technologies, I.e., information extraction, constraint satisfaction, iterative scheduling »Log, analyze, learn profiles to incrementally improve scheduling

3. 3RADAR – Scheduling Task © 2003 Carnegie Mellon University Calendar Scheduling is Complicated Meeting constraints may be hard to satisfy, requiring counter proposals, or relaxing, or negotiation Pre-emption of a meeting can cause a ripple effect Users do not put all commitments in their calendars It may be necessary to secure additional resources (e.g., room, projection facilities) Preferences and interaction protocols will vary according to context and participants involved There may be several meeting requests in various stages of commitment at any given time

4. 4RADAR – Scheduling Task © 2003 Carnegie Mellon University Diversity and Complexity Can we meet tomorrow at 10am? Can we meet with Pat some time this week? The admissions committee needs to meet every week until the end of February. The interested teaching AI faculty need to meet to schedule the courses for the Fall. We should arrange an AI retreat, as the one we did a few years ago. Templates

5. 5RADAR – Scheduling Task © 2003 Carnegie Mellon University The Approach Email Stream User Knowledge Base Learning Processes Extractor Message Stream Email Stream Preferences and Profiles Editor Calendar Display SchedulerManager Need for “Sliding Autonomy”

6. 6RADAR – Scheduling Task © 2003 Carnegie Mellon University Scheduler: Responding to a Request Request: Template, T »When: Thursday 15th »Duration: 1 hour »Who: Visiting Researcher (Priority: “medium”) »Where: 1502E NSH Response, R: »4:00 - 6:00 Infeasible Commited Pending 11:00 - 12:30 2:00 - 3:00 4:00 - Policy preference: Avoid lunch hour Pending reservation but lower priority … but would 1/2 hour be sufficient? Generate Options Evaluate Options … Preference Order: 4:00 - 6:00 2:00 - 3:00 11:00- 12:00 Threshold

7. 7RADAR – Scheduling Task © 2003 Carnegie Mellon University Manager: Multi-Thread Processing Manuela’s Calendar Manuela Raj Student Steve 10am? Time Meeting request for blocked time 12pm 2pm 4pm Student, Steve 10am ConfirmedPending

8. 8RADAR – Scheduling Task © 2003 Carnegie Mellon University Manager: Multi-Thread Processing Manuela’s Calendar Manuela Raj Student Steve 10am? Resch. 12pm? Time Conflict: try rescheduling 12pm 2pm 4pm Student, Steve 10am ConfirmedPending Raj Student, Steve

9. 9RADAR – Scheduling Task © 2003 Carnegie Mellon University Manager: Multi-Thread Processing Steve’s Calendar Manuela Raj Student Steve 10am? Resch. 12pm? Time Student 12pm 2pm 4pm Student, Manuela 10am ConfirmedPending Conflict: try rescheduling Student, Manuela

10. 10RADAR – Scheduling Task © 2003 Carnegie Mellon University Manager: Multi-Thread Processing Student’s Calendar Manuela Raj Student Steve 10am? Resch. 12pm? 12pm okay Time 12pm 2pm 4pm Manuela, Steve 10am ConfirmedPending No conflict Manuela, Steve

11. 11RADAR – Scheduling Task © 2003 Carnegie Mellon University Manager: Multi-Thread Processing Manuela’s Calendar Manuela Raj Student Steve 10am? Resch. 12pm? 12pm okay 4pm? Time Another meeting 12pm 2pm 4pm Student, Steve 10am ConfirmedPending Raj Brett Student, Steve

12. 12RADAR – Scheduling Task © 2003 Carnegie Mellon University Manager: Multi-Thread Processing Manuela Raj Student Steve 10am? Resch. 12pm? 12pm okay 4pm? 2-4pm better Time Rescheduling difficult: suggest an alternative Steve’s Calendar Student 12pm 2pm 4pm Student, Manuela 10am ConfirmedPending Student, Manuela

13. 13RADAR – Scheduling Task © 2003 Carnegie Mellon University Manager: Multi-Thread Processing Manuela’s Calendar Manuela Raj Student Steve 10am? Resch. 12pm? 12pm okay 4pm? 2-4pm better 2pm? Time Choose best alternative 12pm 2pm 4pm Student, Steve 10am ConfirmedPending Raj Brett Student, Steve

14. 14RADAR – Scheduling Task © 2003 Carnegie Mellon University Student’s Calendar Manager: Multi-Thread Processing Manuela Raj Student Steve 10am? Resch. 12pm? 12pm okay 4pm? 2-4pm better 2pm? 2pm okay Time Pending 12pm 2pm 4pm Manuela, Steve 10am ConfirmedPending Manuela, Steve

15. 15RADAR – Scheduling Task © 2003 Carnegie Mellon University Manager: Multi-Thread Processing Manuela’s Calendar Manuela Raj Student Steve 10am? Resch. 12pm? 12pm okay 4pm? 2-4pm better 2pm? 2pm okay 2pm confirmed 10am confirmed Time 12pm Student, Steve 2pm 4pm Raj 10am ConfirmedPending Brett Confirmed

16. 16RADAR – Scheduling Task © 2003 Carnegie Mellon University Main Tasks RESPONDING to a request for availability »Multi-thread conflicting: –request, availability, response, reschedule INITIATING organizing a meeting »Request meeting »Collect replies »Merge and solve scheduling »Until solution is found LEARNING »Priorities, contexts, profiles

17. 17RADAR – Scheduling Task © 2003 Carnegie Mellon University Manager and Scheduler Manager Email Extractor Email Generator Scheduler Knowledge Base Preferences Profiles R* TT … T T Pending T … … History mtg i T

18. 18RADAR – Scheduling Task © 2003 Carnegie Mellon University Manager and Scheduler Manager Email Extractor Email Generator Scheduler Knowledge Base T Pending T … mtg i+1 … … History mtg i T R* TT … T T’

19. 19RADAR – Scheduling Task © 2003 Carnegie Mellon University The Science Algorithms »Dynamic, incremental constraint-based reasoning »Priority-, preference-driven minimum disruption optimization Main open questions »How to effectively computer assist a user in calendar management? »How to represent and exploit an ill-structured set of calendar scheduling preferences and profiles? »How to learn these preferences and profiles from episodic logging? Novel ideas for open questions »Collaborative meeting scheduling based on context and history –Acquired preferences in different contexts –Acquired beliefs of scheduling preferences of others –Determination of profiles for management »Use of learned profiles to overcome user burden managing calendar »Direct, closed loop integration with user email stream

20. 20RADAR – Scheduling Task © 2003 Carnegie Mellon University Learning Accumulation of episodes Control learning – State/action models Probabilistic dependencies Statistical strategy selection Multiagent learning

21. 21RADAR – Scheduling Task © 2003 Carnegie Mellon University The Impact Scientific advances »Continuous mixed-initiative scheduling »Multi-threaded process management and logging »Learning of interaction preferences and profiles »Seamless integration of scheduler, manager, learner Performance »Full implementation – RADAR improves user’s activity GEMs – Generalized modules for similar activity management – extend to space task

22. 22RADAR – Scheduling Task © 2003 Carnegie Mellon University The Plan Next Steps »Collecting data from the team »Templates as a stub for email extractor »Representation of scheduling preferences and profiles »Assemble architecture: –Scheduler, manager, knowledge base, user, learner »Scheduling engine »Logging of scheduling process Long Run »Learning over collected data »Development of protocols and algorithms for distributed resolution of scheduling conflicts »Multiagent collaboration and sharing among EPCAs