場所：国立情報学研究所(NII) 20階講義室1(2005) （地図）
お問い合わせ：石川 冬樹 (f-ishikawa_AT_nii.ac.jp)_AT_を＠に書き換えてください。
Rina Dechter, University of California, Irvine
Recent Advances in Solving Combinatorial Optimization Tasks over Graphical Models (Joint work with Radu Marinescu)
In this talk I will present state of the art algorithms for solving combinatorial optimization tasks defined over graphical models (Bayesian networks, Markov networks, and constraint networks) and demonstrate their performance on a variety of benchmarks.
Specifically I will present branch and bound and best-first search algorithms which explore the AND/OR search space over graphical models and will demonstrate the gain obtained by exploiting problem’s decomposition (using AND nodes), equivalence (by caching) and irrelevance (via the power of new lower bound heuristics such as mini-buckets). The impact of additional principles such as exploiting determinism via constraint propagation, the use of good initial upper bounds generated via stochastic local search and the variable orderings ideas may be discussed, as time permits.
Rina Dechter is a professor of Computer Science at the University of California, Irvine. She received her PhD in Computer Science at UCLA in 1985, a MS degree in Applied Mathematic from the Weizmann Institute and a B.S in Mathematics and Statistics from the Hebrew University, Jerusalem. Her research centers on computational aspects of automated reasoning and knowledge representation including search, constraint processing and probabilistic reasoning.
Professor Dechter is an author of “Constraint Processing” published by Morgan Kaufmann, 2003, has authored over 100 research papers, and has served on the editorial boards of: Artificial Intelligence, the Constraint Journal, Journal of Artificial Intelligence Research and Logical Method in Computer Science (LMCS). She was awarded the Presidential Young investigator award in 1991, is a fellow of the American association of Artificial Intelligence, she was a Radcliffe fellow 2005-06 and the “Association of Constraint Programming” award (ACP 2007) for research excellence.
Hiroshi Hosobe, National Institute of Informatics
Exploring the Power of Soft Constraints
Constraints provide an effective means for the high-level modeling and reasoning of various problems. In particular, soft constraints are useful since they treat over-constrained problems that naturally arise in real-life applications. In this talk, I will present my nearly two-decade efforts to explore the power of soft constraints.
Especially, I will describe research on constraint hierarchies for graphical systems, speculative constraint processing for multi-agent systems, and concurrent constraint programming for hybrid dynamical systems.
Hiroshi Hosobe is an Associate Professor at the National Institute of Informatics. His research interests include constraint programming, user interfaces, information visualization, computer graphics, multi-agent systems, and hybrid dynamical systems. He was presented with the Takahashi Award in 2003 by the Japan Society for Software Science and Technology.