Heuristic decision making, that is, decision making based on approximate reasoning, is a very important part of our cognition and humans are capable of figuring out effective heuristics for a rather wide palette of decision problems.
Heuristic decision making, that is, decision making based on approximate reasoning, is a very important part of our cognition and humans are capable of figuring out effective heuristics for a rather wide palette of decision problems. Heuristics are also heavily used by machines to guide the search processes of solving NP-hard problems of interest. Unlike humans, however, the machines were not expected to "figure out" a heuristic for a given problem, but just to use the heuristics provided by human operators. Considering this situation, a natural (and economically very important) question is thus whether we can possibly build machines capable of automatically devising heuristics for problems they have never seen before? For years, the prospects of such fully unsupervised heuristic decision making were discussed in the literature with a heavy pessimism.
Over the last two decades, however, things changed dramatically, taking unsupervised heuristic decision making from being a crazy dream to advancing the state of the art in industrial autonomous systems. In fact, with the more complicated decision problems, the machines appear to be as effective as human "heuristic engineers", and sometimes much more effective! In this talk, we'll start with a (very speedy but reasonably comprehensive) overview of two seemingly unrelated concepts: heuristic decision making and model-based problem solving. We then connect between these two concepts, diving into the key representational and algorithmic ingredients (and success stories) of unsupervised heuristic decision making. In particular, along this journey I hope to show you that research in this area can be both mathematically/algorithmically rigorous, and empirically fun, and valuable in practice.
Carmel Domshlak is Associate Professor at the Technion, Israel Institute of Technology, in the Faculty of Industrial Engineering and Management. He is the Director of the Technion-Microsoft Center for E-Commerce Research, a founder of the Business Intelligence Lab. He holds Ph.D. in computer science, and prior to joining the Technion, he spent two years at Cornell University. The research of Carmel Domshlak is mainly devoted to computational and knowledge representation problems in the field of Artificial Intelligence, with a strong emphasis on problems of automated sequential decision making for autonomous systems. His other research interests include modeling and reasoning about preferences and multi-agent interactions, information analysis, and information retrieval. He received the 2009 JAIR-IJCAI Best Paper Prize, and ICAPS-2008, ICAPS-2009, and ECAI-2014 Best Paper awards. He is Associate Editor for the Journal of Artificial Intelligence Research (JAIR), Editorial Board member for Artificial Intelligence journal, and a co-chair of ICAPS-2015 conference.
Its program consists of a one-hour lecture followed by a discussion. The lecture is based on an (internationally) exceptional or remarkable achievement of the lecturer, presented in a way which is comprehensible and interesting to a broad computer science community. The lectures are in English.
The seminar is organized by the organizational committee consisting of Roman Barták (Charles University, Faculty of Mathematics and Physics), Jaroslav Hlinka (Czech Academy of Sciences, Computer Science Institute), Michal Chytil, Pavel Kordík (Czech Tech. Univ., Faculty of Information Technologies), Michal Koucký (Charles University, Faculty of Mathematics and Physics), Jan Kybic (Czech Tech. Univ., Faculty of Electrical Engineering), Michal Pěchouček (Czech Tech. Univ., Faculty of Electrical Engineering), Jiří Sgall (Charles University, Faculty of Mathematics and Physics), Vojtěch Svátek (University of Economics, Faculty of Informatics and Statistics), Michal Šorel (Czech Academy of Sciences, Institute of Information Theory and Automation), Tomáš Werner (Czech Tech. Univ., Faculty of Electrical Engineering), and Filip Železný (Czech Tech. Univ., Faculty of Electrical Engineering)
The idea to organize this seminar emerged in discussions of the representatives of several research institutes on how to avoid the undesired fragmentation of the Czech computer science community.