The usually sensible people at MIT's Senseable City Lab are looking at the future of the traffic light in the world of the self-driving car, and predict that its days are numbered. Instead, they propose a "slot-based intersections that could replace traditional traffic lights, significantly reducing delays, make traffic patterns more efficient, and lower fuel consumption." It's based on the principle that if all the self-driving cars are communication with each other and know they all are, they can plan speeds and courses so that they essentially pass through each other. Upon approaching an intersection, a vehicle automatically contacts a traffic management system to request access. Each self-driving vehicle is then assigned an individualized time or "slot" to enter the intersection.

The Lost World: Jurassic Park 1997 AMC Sun. Tomorrow Never Dies 1997 EPIX Wed. 10 p.m., Thur. The X-Files: Fight the Future 1998 IFC Thur. Hard to Kill 1990 Sundance Mon. 8 p.m., Tue. A scientist gives his bodyguard superhuman powers in order to fight racists. A lawyer unwittingly becomes friends with an unstable woman who has a criminal history. A successful businesswoman puts her family, career and life on the line to satisfy her addiction to sex. With his father trapped in the wreckage of their spacecraft, a youth treks across Earth's now-hostile terrain to recover their rescue beacon and signal for help. In the future a cutting-edge android in the form of a boy embarks on a journey to discover his true nature. An 11-year-old boy experiences the worst day of his young life but soon learns that he's not alone when other members of his family encounter their own calamities. A struggling writer falls in love with a stenographer while trying to finish his new novel in 30 days.

KGoldrunner is a puzzle-oriented platform game with dynamic elements. This paper describes Goldspinner, an automatic level generation system for KGoldrunner. Goldspinner has two parts: a genetic algorithm that generates candidate levels, and simulations that use an AI agent to attempt to solve the level from the player's perspective. Our genetic algorithm determines how "good" a candidate level is by examining many different properties of the level, all based on its static aspects. Once the genetic algorithm identifies a good candidate, simulations are performed to evaluate the dynamic aspects of the level. Levels that are statically good may not be dynamically good (or even solvable), making simulation an essential aspect of our level generation system. By carefully optimizing our genetic algorithm and simulation agent we have created an efficient system capable of generating interesting levels in real time.

This paper is concerned with algorithms for prediction of discrete sequences over a finite alphabet, using variable order Markov models. The class of such algorithms is large and in principle includes any lossless compression algorithm. We focus on six prominent prediction algorithms, including Context Tree Weighting (CTW), Prediction by Partial Match (PPM) and Probabilistic Suffix Trees (PSTs). We discuss the properties of these algorithms and compare their performance using real life sequences from three domains: proteins, English text and music pieces. The comparison is made with respect to prediction quality as measured by the average log-loss. We also compare classification algorithms based on these predictors with respect to a number of large protein classification tasks. Our results indicate that a "decomposed" CTW (a variant of the CTW algorithm) and PPM outperform all other algorithms in sequence prediction tasks. Somewhat surprisingly, a different algorithm, which is a modification of the Lempel-Ziv compression algorithm, significantly outperforms all algorithms on the protein classification problems.

Logical hidden Markov models (LOHMMs) upgrade traditional hidden Markov models to deal with sequences of structured symbols in the form of logical atoms, rather than flat characters. This note formally introduces LOHMMs and presents solutions to the three central inference problems for LOHMMs: evaluation, most likely hidden state sequence and parameter estimation. The resulting representation and algorithms are experimentally evaluated on problems from the domain of bioinformatics.

This paper is concerned with algorithms for prediction of discrete sequences over a finite alphabet, using variable order Markov models. The class of such algorithms is large and in principle includes any lossless compression algorithm. We focus on six prominent prediction algorithms, including Context Tree Weighting (CTW), Prediction by Partial Match (PPM) and Probabilistic Suffix Trees (PSTs). We discuss the properties of these algorithms and compare their performance using real life sequences from three domains: proteins, English text and music pieces. The comparison is made with respect to prediction quality as measured by the average log-loss. We also compare classification algorithms based on these predictors with respect to a number of large protein classification tasks. Our results indicate that a ``decomposed'' CTW (a variant of the CTW algorithm) and PPM outperform all other algorithms in sequence prediction tasks. Somewhat surprisingly, a different algorithm, which is a modification of the Lempel-Ziv compression algorithm, significantly outperforms all algorithms on the protein classification problems.

(ICKEDS 2004). This book looks at some of the results of the synergy among AI, cognitive science, and education. Examples include virtual students whose misconceptions force students to reflect on their own knowledge, intelligent tutoring systems, and speech-recognition technology that helps students learn to read. Some of the systems described are already used in classrooms and have been evaluated; a few are still laboratory efforts. The book also addresses cultural and political issues involved in the deployment of new educational technologies.

NASA Ames Research Center Polish Academy of Sciences URL: www.taai.org.tw/announce/ (PRICAI 2004). (ICKEDS 2004). This book looks at some of the results of the synergy among AI, cognitive science, and education. Examples include virtual students whose misconceptions force students to reflect on their own knowledge, intelligent tutoring systems, and speech recognition technology that helps students learn to read.

The seventh biennial Bar-Ilan International Symposium on the Foundations of Artificial Intelligence, will be held on June 25-27, 2001 in Ramat Gan, Israel. The meeting will honor the research and accomplishments of Yaacov Choueka and will therefore place special emphasis on natural language processing and computational linguistics, in addition to the usual topics of the symposium. Yaacov Choueka Jieh Hsiang Daphne Koller Richard Korf Doug Lenat Moshe Vardi The BISFAI-01 program, schedule and registration information will be available at the BISFAI website: www.cs.biu.ac.il/ bisfai, along with abstracts of invited and accepted papers and pointers to online versions.For further information or requests, contact: bisfai@cs.biu.ac.il. CONTEXT-01 EST Setubal, Campus do IPS / R. Vale www.dfki.de/um2001 Faculty Positions for Intelligent Aerospace Systems Program The College of Engineering at the University of Oklahoma invites applications for 3 to 5 new faculty positions at all levels in the area of Intelligent Systems.

It comprises activities Systems, Knowledge Representation managing an interaction. On the focused on the organization, acquiring and Reasoning, and Knowledge Discovery. Wide Web and will remain available in any system that aims to tutor users The KM community has been at ksi.cpsc.ucalgary.ca/AIKM97. Cross-language text retrieval (CLTR) is the problem of matching a query in The presentations made at this symposium This symposium brought together one language to related documents in dealt with vastly different environments, researchers in natural language processing other languages. As internet resources ranging from digital libraries (NLP) from both academia such as the World Wide Web have and broadcast news archives to virtual and industry, including service become global networks, many new reality and, of course, the web.