RADAR – Scheduling Task
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Transcript of RADAR – Scheduling Task
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)
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
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
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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
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The Approach
Email Stream
User
KnowledgeBase
LearningProcesses
ExtractorMessage Stream
Email Stream
Preferencesand Profiles
EditorCalendarDisplay
SchedulerManager
Need for “Sliding Autonomy”
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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 - 6:002:00 - 3:00
11:00- 12:00
Threshold
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Manager: Multi-Thread Processing
Manuela’s Calendar
Manuela
Raj
Student
Steve
10am?
Time
Meeting request for blocked time
12pm
2pm
4pm
Student, Steve10am
Confirmed Pending
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Manager: Multi-Thread Processing
Manuela’s Calendar
Manuela
Raj
Student
Steve
10am?
Resch. 12pm?
Time
Conflict: try rescheduling
12pm
2pm
4pm
Student, Steve10am
Confirmed Pending
Raj
Student, Steve
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Manager: Multi-Thread Processing
Steve’sCalendar
Manuela
Raj
Student
Steve
10am?
Resch. 12pm?
Time
Student12pm
2pm
4pm
Student, Manuela10am
Confirmed Pending
Conflict: try rescheduling
Student, Manuela
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Manager: Multi-Thread Processing
Student’s Calendar
Manuela
Raj
Student
Steve
10am?
Resch. 12pm?
12pmokay
Time
12pm
2pm
4pm
Manuela, Steve10am
Confirmed Pending
No conflict Manuela, Steve
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Manager: Multi-Thread Processing
Manuela’s Calendar
Manuela
Raj
Student
Steve
10am?
Resch. 12pm?
12pmokay
4pm?
Time
Another meeting 12pm
2pm
4pm
Student, Steve10am
Confirmed Pending
Raj
Brett
Student, Steve
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Manager: Multi-Thread Processing
Manuela
Raj
Student
Steve
10am?
Resch. 12pm?
12pmokay
4pm?
2-4pm better
Time
Rescheduling difficult: suggest an alternative Steve’s
Calendar
Student 12pm
2pm
4pm
Student, Manuela10am
Confirmed Pending
Student, Manuela
Student, Manuela
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Manager: Multi-Thread Processing
Manuela’s Calendar
Manuela
Raj
Student
Steve
10am?
Resch. 12pm?
12pmokay
4pm?
2-4pm better 2pm?
Time
Choose best alternative 12pm
2pm
4pm
Student, Steve10am
Confirmed Pending
Raj
Brett
Student, Steve
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Student’s Calendar
Manager: Multi-Thread Processing
Manuela
Raj
Student
Steve
10am?
Resch. 12pm?
12pmokay
4pm?
2-4pm better 2pm?
2pmokay
Time
Pending 12pm
2pm
4pm
Manuela, Steve10am
Confirmed Pending
Manuela, Steve
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Manager: Multi-Thread Processing
Manuela’s Calendar
Manuela
Raj
Student
Steve
10am?
Resch. 12pm?
12pmokay
4pm?
2-4pm better 2pm?
2pmokay
2pmconfirmed
10amconfirmed
Time
12pm
Student, Steve2pm
4pm
Raj10am
Confirmed Pending
Brett
Confirmed
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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
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Manager and Scheduler
Manager
EmailExtractor
EmailGenerator
Scheduler
Knowledge Base
• Preferences• Profiles
R*
T T … T
T
Pending
T …
…History
mtg i
T
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Manager and Scheduler
Manager
EmailExtractor
EmailGenerator
Scheduler
Knowledge Base
T
Pending
T …
mtg i+1 ……
History
mtg i
T
R*
T T … T
T’
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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
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Learning
• Accumulation of episodes
• Control learning – State/action models
• Probabilistic dependencies
• Statistical strategy selection
• Multiagent learning
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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
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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