Third International Workshop on Experimental Economics and Machine Learning

The Third International Workshop on 
Experimental Economics and Machine Learning (EEML 2014)
as a part of ECML PKDD 2014 workshop program

Call for Papers

Description of the workshop:

It is not only the global financial crisis of the recent years [G. P. Maxton, The end of progress : how modern economics has failed us. John Wiley & Sons, 2011.], which made economists reconsider the path economics as a discipline should take. Since decades, it became obvious that classical theories fail in real world [D. Ariely, Predictably Irrational. Harper, 2009.]. Paul Krugman described the current situation in economics as: "... the central cause of the profession’s failure was the desire for an all-encompassing, intellectually elegant approach that also gave economists a chance to show off their mathematical prowess. Unfortunately, this romanticized and sanitized vision of the economics led most economists to ignore all the things that can go wrong. They turned a blind eye to the limitations of human rationality". Experimental Economics gained its importance as a promising solution of this problem. Human being a subject of research has shifted economists' point of view closer to the psychologists' one: people are no more considered to be rational payoff maximizers. On the other side, growing size and complexity of the data makes the application of state-of-the-art data science essential.In Experimental Economics, laboratory and field experiments are carried out using human subjects in order to improve theoretical knowledge about human behavior during interaction. Although financial rewards restrict subjects' preferences in the experiments, the exclusive application of analytical game theory is not enough to explain the collected data. It calls for the development and evaluation of more sophisticated models. Additionally, the research area includes experiments where human subjects are involved into interaction with automated agents.The more data is used for evaluation, the more statistical significance can be achieved. Since large amounts of behavioral data are required to scan for regularities, along with automated agents needed to simulate and intervene in human interactions, Machine Learning is the tool of choice for research in Experimental Economics. This workshop is aimed at bringing together researchers from both Data Analysis and Economics in order to achieve mutually-beneficial results.

As a part of the renowned international conferrence ECML PKDD 2014 focusing on different branches of Machine Learning, this full-day workshop intends to bridge the gap between two scientific communities: Experimental Economics and AI & Data Mining. The first workshop – EEML 2012 – has been successfully accomplished at ICFCA 2012. The second workshop – EEML 2013 – was held alongside the IEEE ICDM 2013. We hope that this year we can continue our work and encourage even more interaction among the researchers from these two fields.

Subject coverage:

• Economic Applications of Machine Learning
• Economic Innovations and Data Mining
• Experimental Economics and Complex Networks
• Econometrics VS Machine Learning & Data Mining
• Human Behavior Modeling and Game Theory
• Innovative applications of Concept Lattices in Economics & Data Mining
• Interdisciplinary Data Science
• Knowledge Discovery in Economics Domain
• Natural Language Processing in Economics Domain
• Machine Learning for Social Sciences
• New Modeling Languages for Economics  (Bayes and Markov Nets, Petri Nets etc.)
• Ontologies for Economics
• Real Data Mining Projects

Important dates

Submissions

The workshop proceedings will be included into a joint publication as CCIS series of Springer, for which workshop chairs will file soon. A publication on CEUR-WS is guaranteed anyway.

1) Paper submissions are limited to a maximum of 12 pages, and follow the Springer format requirements
http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0

2) Submissions can be done over
https://www.easychair.org/conferences/?conf=eeml2014

3) Each submitted paper is to be carefully reviewed by at least two, preferably three, knowledgeable and experienced reviewers.
4) Every accepted paper is invited to be presented at the workshop date.

Workshop co-chairs

Dmitry Ignatov, National Research University Higher School of Economics, Russia

Boris Gutkin, Group for Neural Theory, Ecole Normale Superieure, France (to be confirmed)

Fadi Amroush, Granada Lab of Behavioral Economics (GLOBE), Spain

Tentative Program Committee (to be extended and confirmed)

Aleksandr Karpov, National Research University Higher School of Economics, Russia

Alexander Panchenko, Université catholique de Louvain, Belgium

Amedeo Napoli, Loria, Nancy, France

Antonio Gabriel López Herrera, Department of Computer Science and Artificial Intelligence, Spain

Boris Galitsky, e-Bay Inc, USA

Boris Mirkin, National Research University Higher School of Economics, Russia

Daniel Karabekyan, National Research University Higher School of Economics, Russia

Guido Dedene, Katholieke Universiteit Leuven, Belgium

Heather D. Pfeiffer, Akamai Physics Inc., USA

Henry I. Penikas, National Research University Higher School of Economics, Russia

Irina Efimenko, National Research University Higher School of Economics, Russia

Jonas Poelmans, Kathoelike Universiteit, Belgium

Leonid Zhukov, National Research University Higher School of Economics, Russia

Malay Bhattacharyya, Indian Statistical Institute, Kolkata, India

Mehdi Kaytoue, INSA, Lyon, France

Mikhail Khachay, Institute of Mathematics and Mechanics, Ural Branch of RAS, Ekaterinburg, Russia

Mykola Pechenizkiy, Eindhoven Technical University, The Netherlands

Natalia Konstantinova, University of Wolverhampton, UK

Nicola Vitucci, Politecnico di Milano, Italy

Nikolaos Georgantzis,University of Granada & Universitat Jaume I, Spain

Olga Barinova, Moscow State University, Russia

Paul Elzinga, Katholieke Universiteit Leuven, Belgium and Amsterdam-Amstelland police, The Netherlands

Pouya Dehghani Tafti, Alumni of EPFL, Switzerland

Rostislav Yavorskiy, Higher School of Economics, Russia

Sergei Kuznetsov, National Research University Higher School of Economics, Russia

Sergei Nikolenko, National Research University Higher School of Economics, Russia

Simon Andrews, Sheffield Hallam University, UK

Simon Polovina, Sheffield Hallam University, UK

StijnViaene, Vlerick Leuven Management School, Katholieke Universiteit Leuven, Belgium

Stephan Alexander Rompf, Alumni of University of Mannheim, Germany

Sushmita Mitra, Indian Statistical Institute, Kolkata, India

Tania Garfias Macedo, Alumni of University of Goettingen, Germany

T.L. Hoang, Eindhoven Technical University, The Netherlands

Vladimir Khoroshevsky, Computing Centre of Russian Academy of Sciences, Russia

Vlado Menkovski, Eindhoven Technical University, The Netherlands

Xenia Naidenova, Military Medical Academy, St. Petersburg, Russia

Short biographies of the organizers

Dr. Rustam Tagiew obtained PhD with distinction (Doctor rerum naturalium, Magna Cum Laude) in 2011 from University of Freiberg specializing in computer modeling of strategic human interaction. The topic of the thesis is highly interdisciplinary; it encompasses a variety of disciplines such as multi-agent systems, formal methods, data mining, game theory, experimental economics (especially human behavior modeling) and psychology. He authored about 20 publications on the topic. Rustam graduated from University of Bielefeld in 2007 as a Master of Computer science with distinction. During his PhD studies Rustam was supported by different scientific foundation (AISB Student Travel Award for ICCM in Manchester, DAAD-Grants etc.). Rustam is an experienced co-organizer and PC Member of different scientific events (EEML 2012, CDUD 2011 and 2012, SCAKD 2011, Workshop on Real Agents’ Strategic Interaction 2010, AIST 2012 conference etc.). After completion of his postdoctoral program he is working for Data Mining company, Qlaym GmbH (Dusseldorf), as a researcher. One of his main scientific beliefs is the following: gathering and analyzing data is important to compensate the inadequacies of game theory in prediction of human behavior.

(a longer CV version: http://de.linkedin.com/in/tagiew)

Dr. Dmitry Ignatov works as an Associate Professor for the National Research University "Higher School of Economics" (Moscow, Russia) at the department of Artificial Intelligence and Data Analysis. Dr. Dmitry Ignatov graduated in 2004 as a “Specialist in Physics and Mathematics” with distinction (Kolomna, Russia) and in 2008 as a “Master of Applied Mathematics and Information Sciences” at the “State University Higher School of Economics” (Russia, Moscow). In 2010 he obtained his degree of “Candidate of sciences in Mathematical Modeling, Numerical Methods, and Software Systems” at the “National Research University Higher School of Economics”. He did his PhD (Candidate of science in Russian) research in All-Russian Institute for Scientific and Technical Information of Russian Academy of sciences specializing in Theoretical Computer Science. He is an author of more than 35 papers published in peer reviewed conferences, workshops and journals. His main interests include Formal Concept Analysis, Data Mining and Machine Learning, especially biclustering and multimodal clustering in Collaborative Filtering. He was a co-organizer or a program co-chair of several international conferences and workshops: ECIR 2013, ICFCA 2012, ICCS 2009 and 2013, RSFDGrC 2011, PReMI 2011, CDUD 2011 and 2012, EEML 2012, SCAKD 2011, AIST 2012, 2013 and 2014 etc.

(a personal webpage: http://www.hse.ru/en/org/persons/228204)

Dr. Fadi Amroush received a post doctorate scholarship for the University of Salamanca at the department of Economics. Dr. Fadi Amroush graduated in 2005 as a “Bachelor of Informatics Engineering” at the University of Aleppo (Syria), and in 2009 as a “Master of Informatics Engineering” at the University of Aleppo (Syria). In 2009 he received an Erasmus Mundus scholarship at the University of Granada, Spain. Fadi completed a Master’s Degree and a PhD in Economics at the University of Granada, Spain. Fadi was the laboratory manager of the experimental economics laboratory at the University of Granada (EGEO). His PhD thesis was an interdisciplinary study combining experimental economics and decision-making theories with methodology from the area of artificial intelligence. His main interests include product selection, decision making systems, understanding and investigating experimentally how people select products, and applying different models of decision support systems.

(a personal webpage: http://ideas.repec.org/e/pam102.html)

Dr. Boris Gutkin is a team leader of the Group for Neural Theory (INSERM U960, DEC, ENS, Paris) since 2008 and Senior Research Scientist, Departement de Neuroscience, Institut Pasteur, Paris since 2004. Before he held positions as a Senior Research Scientist at GNT, Department of Cognitive Studies, Ecole Normale Superior and College de France, Paris (2005-2008) and as a Senior Research Fellow, Gatsby Computational Neuroscience Unit, University College London (2002-2004).

Boris finished his Ph.D. in Theoretical Neuroscience, March 1999, University of Pittsburgh and Center for Neural Basis of Cognition, Pittsburgh, PA and previously received following degrees:

M.A. Mathematics, May 1996, University of Pittsburgh, Pittsburgh, PA

M.S. Biomathematics, December 1993, North Carolina State University, Raleigh, NC

B.S. Physics/History (cum laude) May 1989, North Carolina State University, Raleigh, NC.

His research interests lie in computational and mathematical approaches to understanding neural function and cognition. Research interests of the group are wide ranging, carried out in collaboration with the experimental labs at the research center and the faculty of applied mathematics. Research themes include models of social decision making, computational neuroeconomics, information processing in neurons and circuits as well as computational approaches to drug addiction and role of oscillations in cognition. (a personal webpage: http://www.gnt.ens.fr/people.php?id=2)

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