The SciFinance software synthesis system, licensed to major investment banks, automates programming for financial risk-management activities -- from algorithms research to production pricing to risk control. SciFinance's high-level, extensible specification language, aspen, lets quantitative analysts generate code from concise model descriptions written in application-specific and mathematical terminology; typically, a page or less produces thousands of lines of c. aspen's abstractions help analysts focus on their primary tasks -- model description, validation, and analysis -- rather than on programming details. Compared with manual programming, automation produces codes that are more sophisticated, accurate, and consistent. The shared knowledge base is used by the specification checker, synthesis system, and information portal.

Unsupervised Learning: Foundations of Neural Computation is a collection of 21 papers published in the journal Neural Computation in the 10-year period since its founding in 1989 by Terrence Sejnowski. Neural Computation has become the leading journal of its kind. The editors of the book are Geoffrey Hinton and Terrence Sejnowski, two pioneers in neural networks. The selected papers include some of the most influential titles of late, for example, "What Is the Goal of Sensory Coding" by David Field and "An Information-Maximization Approach to Blind Separation and Blind Deconvolution" by Anthony Bell and Terrence Sejnowski.

The Fourth International Conference on Autonomous Agents

This article describes the winning entries in the 2000 Association for the Advancement of Artificial Intelligence Mobile Robot Competition. The robots, developed by Swarthmore College, all used a modular hybrid architecture designed to enable reflexive responses to perceptual input. Within this architecture, the robots integrated visual sensing, speech synthesis and recognition, the display of an animated face, navigation, and interrobot communication.

Like the well-known hsp system, FF relies on forward search in the state space, guided by a heuristic that estimates goal distances by ignoring delete lists. Humans have a remarkable capability to perform a wide variety of physical and mental tasks without any measurements and any computations. In more concrete terms, perceptions are f-granular, meaning that (1) the boundaries of perceived classes are unsharp and (2) the values of attributes are granulated, with a granule being a clump of values (points, objects) drawn together by indistinguishability, similarity, proximity, and function. The computational theory of perceptions (CTP), which is outlined in this article, adds to the armamentarium of AI a capability to compute and reason with perception-based information.

The Third International Conference on Case-Based Reasoning was held at the Seeon Monastery, Bavaria, 27 to 30 July 1999. About 120 researchers from 21 countries attended. The conference included 4 workshops; 3 invit-ed talks; 24 technical presentations; a poster session; and an Industry Day, where the focus was on mature technologies and applications in industry.

The AAAI-2000 Workshop Program was held Sunday and Monday, 3031 July 2000 at the Hyatt Regency Austin and the Austin Convention Center in Austin, Texas. The 15 workshops held were (1) Agent-Oriented Information Systems, (2) Artificial Intelligence and Music, (3) Artificial Intelligence and Web Search, (4) Constraints and AI Planning, (5) Integration of AI and OR: Techniques for Combinatorial Optimization, (6) Intelligent Lessons Learned Systems, (7) Knowledge-Based Electronic Markets, (8) Learning from Imbalanced Data Sets, (9) Learning Statistical Models from Rela-tional Data, (10) Leveraging Probability and Uncertainty in Computation, (11) Mobile Robotic Competition and Exhibition, (12) New Research Problems for Machine Learning, (13) Parallel and Distributed Search for Reasoning, (14) Representational Issues for Real-World Planning Systems, and (15) Spatial and Temporal Granularity.

We are interested in solving real-world planning problems and, to that end, argue for the use of domain knowledge in planning. We believe that the field must develop methods capable of using rich knowledge models to make planning tools useful for complex problems. In particular, we compare knowledge rich approaches such as hierarchical task network planning to minimal-knowledge methods such as STRIPS-based planners and disjunctive planners. Finally, we draw an analogy from the current focus of the planning community on disjunctive planners to the experiences of the machine learning community over the past decade.

The Fourth Robotic Soccer World Championships (RoboCup-2000) was held from 27 August to 3 September 2000 at the Melbourne Exhibition Center in Melbourne, Australia. RoboCup-2000 showed dramatic improvement over past years in each of the existing robotic soccer leagues (legged, small size, mid size, and simulation) and introduced RoboCup Jr. competitions and RoboCup Rescue and Humanoid demonstration events. The RoboCup Workshop, held in conjunction with the championships, provided a forum for the exchange of ideas and experiences among the different leagues. This article summarizes the advances seen at RoboCup-2000, including reports from the championship teams and overviews of all the RoboCup events.

The Thirteenth Annual International Conference of the Florida Artificial Intelligence Research Society was held in Orlando, Florida, on 22 to 24 May. The conference included sessions on 11 topics. The session on validation, verification, and system certification was the most extensive. The conference also included panel discussions and invited talks by Subrata Dasgupta, Jim Hendler, and Janet Kolodner.