First International Workshop on:

Optimisation in Multi-Agent Systems

(OptMas)

 To be held in conjunction with the
Seventh Joint Conference on Autonomous and Multi-Agent Systems
(AAMAS 2008)
12 May 2008

 

Call

This workshop invites works from different strands of the multi-agent systems community that pertain to the design of algorithms, models, and techniques to deal with multi-agent optimisation problems. In so doing, this workshop aims to provide a forum for researchers to discuss common issues that arise in solving optimisation problems in different areas and elaborate common benchmarks to test their solutions.

Invited Talk: Prof. Moshe Tennenholtz will be giving an invited talk at the workshop.  Click here for a short bio of the speaker.

Background

The number of novel applications of multi-agent systems has followed an exponential trend over the last few years, ranging from online auction design, through in multi-sensor networks, to scheduling of tasks in multi-actor systems. Multi-agent systems designed for all these applications generally require some form of optimization in order to achieve their goal. Given this, a number of advancements have been made in the design of winner determination, coalition formation, and distributed constraints optimization algorithms among others. However, there are no general principles guiding the design of such algorithms that would enable researchers to either exploit solutions designed in other areas or to ensure that their algorithms conform to some level of applicability to real problems.

This workshop aims to address the above issues by bringing together researchers from different parts of the Multi-Agent Systems research area to present their work and discuss acceptable solutions, benchmarks, and evaluation methods for generally researched optimization problems.

In particular, the main issues to be addressed by the workshop will include (but are not limited to):

  1. Techniques to model and solve optimisation problems in which the actors are partly or completely distributed and can only communicate with their peers.
  2. Algorithms to compute solutions to mechanisms that deal with different stakeholders who may be self interested or may have different computation/communication capabilities from their peers.
  3. Dealing with privacy concerns: solving complex optimization problems while leaking as little private information as possible.
  4. Problems that require anytime algorithms.
  5.  Algorithms that need to provide guarantees on the quality of the solution.
  6. Mechanisms whose properties can be significantly affected if the solution computed is not the optimal one.
  7. Techniques to deal with optimizations that have to be repeated with possibly only slight changes in the input data.
  8. Techniques to deal with situations where the input data may be uncertain or unreliable, requiring that the solution computed be robust to slight differences from the true values
  9. General heuristics and approximate solutions to multi-agent optimisation problems.

Keywords

Topics include but are not limited to:

Programme:


Session 1: 9:30-11:00 (Distributed Optimisation I)

  1. Agent Based Decomposition of Optimization Problems

    Johan Holmgren, Jan A. Persson, Paul Davidsson

  2. Optimization in Private Stable Matching with Cost of Privacy Loss

    Marius Silaghi, Prashant Doshi, Toshihiro Matsui, Makoto Yokoo, Markus Zanker

  3. Benchmarking Hybrid Algorithms for Distributed Constraint Optimisation Games

    Archie Chapman, Alex Rogers, Nicholas R. Jennings

Session 2: 11:30-13:00 (Auctions and Coalition Formation + 1 short presentation)

  1. Bidding Strategies for Realistic Multi-Unit Sealed-Bid Auctions

    Ioannis Vetsikas, Nicholas R. Jennings

  2. Optimizing coalition formation for tasks with dynamically evolving rewards and nondeterministic action effects

    Majid Ali Khan, Damla Turgut, Ladislau Boloni

  3. Agent-Based Optimisation Systems for Electrical Load Management

    Rongxin Li, Jiaming Li, Geoff Poulton, Geoff James

  4. A Self-organizing Multi-agent System for Online Unsupervised Learning in Complex Dynamic Environments

    Igor Kiselev, Reda Alhajj


Session 3: 14:30-16:00 (Invited talk + 1 long presentation)


Invited Talk: Moshe Tennenholtz (14:30-15:30)


  1. Stochastic Fictitious Play using Particle Filters to update the beliefs of opponents strategies

    Michalis Smyrnakis, David Leslie

Session 4: 16:30-17:30: (Distributed Optimisation II + 2 Short presentations)

  1. Constant cost of the computation-unit in efficiency graphs

    Marius Silaghi, Robert N. Lass, Evan Sultanik, William Regli, Toshihiro Matsui, Makoto Yokoo

  2. An Organizational View of Metaheuristics

    David Meignan, Jean-Charles Creput, Abderrafiaa Koukam

  3. MANGO: A MultiAgent ENvironment for Global Optimization

    Lirida Kercelli, Ayse Sezer, Pinar Yolum, S.Ilker Birbil, Figen Oztoprak

Session 5: 17:40-18:30 (Panel Session)

Panellists: Nicholas R. Jennings, Moshe Tennenholtz, Makoto Yokoo


Important Dates:

FEBRUARY 1st, 2008 - Submission of contributions to workshops (passed)
MAY 12th 2008 - Workshop takes place in conjunction with AAMAS 2008.

Organising Committee

Prof. Nicholas R. Jennings (University of Southampton, UK)

Adrian Petcu (EPFL, Switzerland)

Dr. Alex Rogers (University of Southampton, UK)

Dr. Sarvapali D. Ramchurn (University of Southampton, UK)

 

Programme Committee

Michael Rothkopf - RUTCOR, State University of New Jersey, USA

Juan Antonio Rodriguez - IIIA, CSIC, Spain

Carles Sierra - IIIA, CSIC, Spain

Paul Scerri - Robotics Institute, CMU, USA

Marius Silaghi - Florida Institute of Technology, USA

Alessandro Farinelli - University of Southampton, UK

Zinovi Rabinovich - University of Southampton, UK

Jesus Cerquides - University of Barcelona, Spain.

Sven Koenig - University of Southern California, USA

David Parkes - Harvard University, USA

Makoto Yokoo - Kyushu University, Japan

Ioannis Vetsikas - University of Southampton, UK

(More to be confirmed)