[agents] CFP: International Workshop on Optimization and Learning in Multi-Agent Systems (at AAMAS-20)

[Fioretto, Ferdinando]

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International Workshop on Optimization and Learning in Multi-Agent Systems (OptLearnMAS)

A full-day workshop at AAMAS 2020.
Workshop date: May 9 or 10, 2020

Website: https://www2.isye.gatech.edu/~fferdinando3/cfp/OptLearnMAS20/
AAMAS Website: https://aamas2020.conference.auckland.ac.nz/

Workshop description

The goal of the workshop is to provide researchers with a venue to explore how to model and solve a variety of multi-agent optimization problems. We seek contributions in the general area of multi-agent optimization, including distributed constraint optimization, coalition formation, optimization under uncertainty, winner determination algorithms in auctions, and algorithms to compute Nash and other equilibria in games. games. This year, the workshop will have a special focus on contributions at the intersection of optimization and learning. For example, agents which use optimization often employ machine learning to predict unknown parameters appearing in their decision problem. Or, machine learning techniques may be used to improve the efficiency of optimization. While submissions across the spectrum of multi-agent optimization are welcome, contributions at the intersection with learning are especially encouraged.

Topics of Interest

  - Optimization for learning agents
  - Learning for multiagent optimization problems
  - Winner determination algorithms in auctions
  - Coalition formation algorithms
  - Scheduling and task allocation problems
  - Algorithms for solving distributed constraint reasoning problems
  - Unified frameworks for distributed constraint reasoning
  - Handling privacy issues in multi-agent systems
  - Algorithms to compute solutions to games (cooperative or non-cooperative)
  - Multi-agent optimization under uncertainty
  - Multi-agent optimization with incomplete or dynamic input data
  - Algorithms for real-time applications
  - GPU for general purpose computations (GPGPU)
  - Multi-core and many-core computing
  - Cloud, distributed and grid computing
  - Online optimization problems in multi-agent systems

Submission

Conference submission site: https://easychair.org/my/conference?conf=optmas20

OptLearnMAS submissions follows the ACM ‘SigConf’ proceedings guidelines (www.acm.org/publications/proceedings-template<http://www.acm.org/publications/proceedings-template>). The AAMAS style file should be used for both full and short papers (see details below). A sample latex file is provided here: AAMAS20Template-submission.zip.
Submissions should include the name(s), affiliations, and email addresses of all authors. We welcome papers that were unsuccessfully submitted to the AAMAS 2020 and IJCAI 2020 technical programs.

Papers will be reviewed by at least 2 program committee members. Criteria for the selection of papers will include technical quality, novelty, significance, and clarity.

Submission Type
  -  Full Papers: Full-length research papers detailing work in progress or work that could potentially be published at a major conference. These papers should not exceed *6* pages (excluding bibliography and appendices).
  - Short Papers: Position or demo papers that describe initial work or an application that has not yet been evaluated on the topics of interest.  These papers should not exceed *3* pages  (excluding bibliography and appendices).

Important dates
  - Feb 10, 2020  (Submission deadline)
  - March 10, 2020  (Notification of acceptance)
  - March 24, 2020  (Camera-ready deadline for informal proceedings)
  - May 9 or 10, 2020  (Workshop dates )

Organizing committee
  - Archie Chapman, University of Queensland
  - Ferdinando Fioretto, Syracuse University
  - Long Tran-Thanh, University of Southampton
  - Bryan Wilder, Harvard University

Program Committee
  - Bo An (Nanyang Technological University)
  - Ana L. C. Bazzan (Universidade Federal do Rio Grande do Sul)
  - Filippo Bistaffa (IIIA-CSIC)
  - Agostino Dovier (University of Udine)
  - Alessandro Farinelli (University of Verona)
  - Rica Gonen (Open University of Israel)
  - Tal Grinshpoun (Ariel University)
  - Katsutoshi Hirayama (Kobe University)
  - Christopher Kiekintveld (University of Texas at El Paso)
  - Sven Koenig (University of Southern California)
  - Duncan McElfresh (University of Maryland, College Park)
  - Ayan Mukhopadhyay (Stanford University)
  - Amnon Meisels (Ben Gurion University of the Negev)
  - Andrew Perrault (Harvard University)
  - Gauthier Picard (Laboratoire Hubert Curien MINES Saint-Etienne)
  - Enrico Pontelli (New Mexico State University)
  - Juan Antonio Rodriguez Aguilar (IIIA-CSIC)
  - Marius Silaghi (Florida Institute of Technology)
  - Mohamed Wahbi (Insight, University College Cork)
  - Harel Yedidsion (University of Texas, Austin)
  - Pan Xu (New Jersey Institute of Technology)
  - Yexiang Xue (Purdue University)
  - Makoto Yokoo (Kyushu University)
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