= Masterthesis: Opponent Models in Bilateral Negotiation =
by Mark Hendrikx.

== Literature Survey ==
The newest version can be found on the [https://mmi.tudelft.nl/svn/timb/Opponent%20Models%20Survey 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 ==
[http://mmi.tudelft.nl/trac/negotiation/wiki/MeetingMinutes 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
   * ~~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)
   * Conclusion (20-04-12)

 * Finished ANAC2012 agent for finals (30-04-12)

 * 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)