Fourth International Workshop on Experimental Economics and Machine Learning (EEML 2017)
Table of contents
September 17-18, 2017
at Dresden University of Technology (TU-Dresden), Germany
Subject Coverage
Workshop concentrates on an interdisciplinary approach to modeling human behavior incorporating data mining and/or expert knowledge from behavioral sciences. Data analysis results extracted from clean data of laboratory experiments can be compared with noisy industrial data-sets from the web e.g.. Insights from behavioral sciences will help data scientists. Behavior scientists will see new inspirations to research from industrial data science. Market leaders in Big Data, as Microsoft, Facebook, and Google, have already realized the importance of experimental economics know-how for their business.
In Experimental Economics, although financial rewards restrict subjects preferences in experiments, 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. 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.
Keywords
Game Theory, Web Mining, Mechanism Design, Behavioral Science, Machine Learning, Business Intelligence, Data Mining, Experimental Economics, Complex Networks, Econometrics, Human Behavior Modeling, Concept Lattices, Behavioral Economics, Data Science, Knowledge Discovery, Text Mining, Social Sciences, Bayes Nets, Markov Nets, Petri Nets, Neural Nets, Decision Trees, Linear Models, Clustering, Ontologies, Real Data, Cognitive Science
Workshop Co-chairs
Rustam Tagiew, Entrepreneur, Ontonovation, Germany
Dmitry Ignatov, Associate Professor,National Research University HSE, Russia
Andreas Hilbert, Professor for Business Intelligence, TU Dresden, Germany
Kai Heinrich, Scientific Assistant, TU Dresden, Germany
Radhakrishnan Delhibabu, Associate Professor, Kazan Federal University, Russia
Important Dates
Final submission deadline: July 30th, 2017
Notification deadline: August 10th, 2017
Camera ready submission deadline: August 20th, 2017
Workshop date: September 17-18, 2017
Submission Procedure
The submission Web page for EEML 2017 is
https://easychair.org/conferences/?conf=eeml2017.
Electronic version of full paper complete with authors’ affiliations should be submitted through the conference electronic submission system. Manuscripts must be prepared with LaTeX or Microsoft Office and should follow the Springer format available at http://www.springer.de/comp/lncs/authors.html.The maximum number of accepted papers by an individual author that can be covered by the workshop’s registration charge is 3. The papers over 12 pages are not allowed.
Venue
Workshop will be held at Technical University of Dresden. Exact location will be announced.
Proceedings
All accepted papers are published online on the CEUR-Workshop web site in Vol-1968, will be indexed by Scopus and also integrated into RePEc.
Previous Workshops
2012
EEML 2012 Proceedings are available at the CEUR-Workshop website.
2013
Second EEML took place in Dallas, TX, USA as a part of the workshop program of IEEE ICDM 2013. EEML 2013 delivered talks are listed on the workshop website and the proceedings can be downloaded from IEEE Xplore as a part of ICDMW 2013.
2016
Third EEML 2016 took place in Moscow, Russia as a part of workshop program of CLA 2016. The proceedings are available over CEUR-Workshop website as and are listed in DBLP.