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Demo aamas-mapp

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Demo for AAMAS 2013

Demo for AAMAS 2013

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  • 1. A Multi-Agent PlanningPlatform (MAPP) for Course Scheduling 23.January, 2013
  • 2. MAPP• What is MAPP – A multi-agent based intelligent planning platform• What can it do – Generates high-quality course timetable based on constraints and optimization algorithms
  • 3. Why a multi-agent approach is needed?• Aiming at same planning problem, different automated planning algorithms may generate different solutions.• Users have different preferences on multiple feasible solutions• In a traditional optimization way, a system has to be run over and over again with different algorithms and configurations to find the best solution, which costs a lot of time.
  • 4. Architecture InformationPresentation Email Result Configuration Layer Solver AgentBusiness Mediator Solver Agent Layer Agent ……Persistence Constraint Constraint Layer Constraint Rules Rules Rules DB
  • 5. How does MAPP work?• Problem scenario and parameters are configured by user.• The mediator agent dispatches optimization task to several solver agents, which adopts different optimization algorithms and configurations.• Multiple solver agents run in parallel or in a serial fashion• Multiple feasible solutions are generated by solver agents• Mediator agent collects and sorts the solutions generated by solver agents.• The highest score solutions were sent to user by email.
  • 6. Configure GradesClick “Grade”, and then you can either delete or change the entry byclicking the corresponding button.
  • 7. Configure SubjectsClick “Subject”, and then you can either delete or change the entry byclicking the corresponding button.
  • 8. Configure RoomsClick “Room” , and then you can either delete or change the entry byclicking the corresponding button.
  • 9. Configure TeachersClick “Teacher” , and then you can either delete or change the entry byclicking the corresponding button.You can change preferred teaching time by clicking ”Change Preference”
  • 10. Configure ClassesClick “Class” , and then you can either delete or change the entry byclicking the corresponding button.
  • 11. Configure Class Subjects• Different classes may have different number of lectures per week for the same subject, and be taught by different teachers. For example, class 1,2,3 may have 3 lectures for Math each week while class 5 and 6 have 2 lectures. The ClassSubject object maintains this kind of information.
  • 12. Configure Class SubjectsClick “ClassSubject” , and then click “Add ClassSubject”,correspondence between class and subject can be configured.
  • 13. Configure Class SubjectsCorrespondence between teacher and ClassSubject will be built in this page.
  • 14. Configure Student Groups• One ClassSubject object may have several student groups. For example, for the “Math for grade 7” ClassSubject, each teacher only teaches one class in each lecture, then each class of this ClassSubject makes a student group respectively.
  • 15. Configure Student GroupEach student group belongs to a ClassSubject, the relationship can beconfigured in this page.
  • 16. Solving started Two agents running in parallelThe solving process can be started now, and multiple solving agents will be run inparallel to solve this problem
  • 17. Final solutions are sent to user via email
  • 18. Evaluation• We implemented two planning algorithms, Tabu Search and Simulate Testing Data Set Anneal Arithmetic, in both Name Value serial and parallel ways.• The testing data set is # Classes taught 8 shown in right hand table. # Teachers for each subject 3 # Available rooms 8 # Lectures for each class per 3 subject
  • 19. Results 250 Response Time(Sec.) Serial Parallel 200 150 100 50 0 1 2 3 4 5 6 7 8 #SubjectsComparison are shown as two response time.First, with the increasing number of subjects, the execution timeincreases monotonically in both strategies. Second, the response time ofparallel strategy is less than that of serial strategy dramatically, whichmeans the performance of parallel approach is better than that of serialapproach.
  • 20. Thank You!

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