Version 175 (modified by mark, 12 years ago) ( diff )

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Masterthesis: Opponent Models in Bilateral Negotiation

by Mark Hendrikx.

Literature Survey

The newest version can be found on the SVN repository

Main Research Questions

  • How to measure the quality of opponent models?
  • Are agents using opponent models "better" than other agents?
  • How do opponent models compare regarding accuracy, convergence, and computational cost?
  • How to create an opponent model which is better than the state-of-the-art?

Meeting

Meeting agendas and minutes

Planning

The datas in the overview below refer to deadlines.

  • Validated all decoupled agents (13-01-12)
  • Study for exam (15-01-12 -> 03-02-12)
  • First version of short paper ACAN (18-02-12)
  • Finished ANAC2012 agent for qualification round (18-03-12)
  • Finished Camera ready of short paper ACAN (13-04-12)
  • Finished editing OM paper (20-04-12)
    • Abstract / Introduction (01-04-12)
    • Preliminaries (03-04-12)
    • OM in automated negotiation (05-04-12)
    • OM Framework (07-04-12)
    • Learning methods for opponent models
    • Learning of OM (12-04-12)
      • Revise
        • Introduction
        • Section 1: Reservation value
        • Section 2: Negotiation deadline
        • Section 3: Issue Preference Order
        • Section 4: Outcome Preference Order
        • Section 5: Bidding Strategy
        • Section 6: Acceptance Strategy
      • Add new papers
        • Short paper
        • Long papers
    • Use of OM (13-04-12)
    • Evaluating OM (14-04-12)
    • OM in ANAC (15-04-12)
    • Quality of OM in ANAC (18-04-12)
      • Test setup
      • Test results evaluation
    • Conclusion (20-04-12)
  • ANAC competition
    • Finished ANAC2012 agent for finals (07-05-12)
    • Wrote paper (6 - 8 pages)
  • Compare accuracy, convergence, and computational cost of existing models (05-05-12)
    • Implement measurement methods per round
    • Create testsetup
    • Analyze data
  • Create a model which is beter than the state of the art
    • Improve frequency model by dynamic learning rate
    • Improve Bayesian model by improving decision function assumption
  • Conference paper about results (30-05-12)
  • Draft of masterthesis (10/06/12)
  • Finish masterthesis (10/07/12)

Attachments (3)

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