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Sent on behalf of Olaf Witkowski - [log in to unmask] Dear all, The submissions are now open for the Fake Life Recognition Contest! The cash prize is USD 1000, and the deadline for submissions will be February 15th, 2020. Got an idea? We want to hear it! Simply submit your Python code and description on: http://tiny.cc/fakelife. It’s easy and painless :) [ Summary ] The problem of identifying living systems from non-living ones is a difficult question, which research fields such as artificial life or origins of life have been trying to address for decades or more. One can probably tell by sight that a walking line of ants is made of living things, while a flowing river is not. Can a computer tell apart living from non-living things as well as we can? The question is not settled in theory, but we had the idea of trying to settle it in practice. We (Lana Sinapayen and Olaf Witkowski) are organizing a *Fake Life Recognition Contest* (supported by AI company Cross Compass Ltd., and co-organized by Cross Labs and ELSI). The competition has just been announced at the ALIFE 2019 conference, in Newcastle, UK. Concretely, a list of unlabeled datasets are made available online. Some are time series of real living systems, and some are generated by non-living systems. Participants can test their algorithms on these public datasets, but their algorithms will be judged based on unreleased datasets. Along with a working algorithm, each participant is required to submit a short description of the underlying theoretical measure (i.e. "What is your theory about to correctly classify these datasets? What is your idea based on?”). [ Goals and context ] We intend this competition as a critical initiative to help Artificial Life research, and drive it in a practical way, just like computational linguistics for example made tremendous progress in the past few decades by setting up well-defined tasks as shared open challenges. Our goal is to contribute to scientific progress in the field. Although the impact on industry is not the main purpose, one may imagine numerous applications in terms of detection of living systems. The contributions from participants will hopefully help progress in refining our mathematical understanding of the nature of living systems, i.e. what life is in contrast to inert matter. This, in turn, is connected to problems of life detection on exoplanets, the detection of extremophiles on Earth, and the origin of life, and the study of synthetic living systems in general. We consider this as a very important yet not much funded research area, relating to fundamental questions about the status and uniqueness of human life and intelligence in the universe. The competition is volunteer-based and open to all, and its introduction to the public will be made as part of the Hybrid Life workshop at the ALIFE 2019 conference in Newcastle, UK (https://2019.alife.org). [ How to participate ] Concretely, the participants simply need to provide two major elements: a code in Python that returns 1 if the data is from a real living system, and 0 if it's not, and a very short PDF description of what's the mathematical measure under the hood. The use of learning algorithms is expressly not allowed, for the obvious reason they would not yield an explanation of why they work. In case of any doubt, please contact the organizers. Please refer to details under the 'participate' tab. The datasets consist in time series of trajectory positions in 2D (those are meant as actual spatial trajectories), which correspond to either artificial or real living systems. Each dataset comes in the form of a 20Mb or so CSV file with 3 columns labelled “t“, “x” and “y”, with 10,000 rows, for time and positions. [ Winner ] A winner's certificate and a cash prize of USD 1000 will be awarded to the best performing algorithm submitted (in case of a tie, the earlier submission will win) with the support of AI company Cross Compass Ltd. There may also be special mentions for creative attempts we receive, to be shared with the Artificial Life research community. Questions? Please contact us at [log in to unmask] Best of luck to all! Lana Sinapayen and Olaf Witkowski -- Olaf Witkowski, Ph.D. | Director of Scientific Affairs & Chief Scientist, Cross Labs, Cross Compass Ltd. | Research Scientist, ELSI, Tokyo Institute of Technology | Lecturer, University of Tokyo | Visiting Member, Institute for Advanced Study | Founding Member, YHouse | Affiliated Researcher, ECCO, Free University of Brussels | https://olafwitkowski.com ######################################################################## To unsubscribe from the CAS list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=CAS&A=1