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Computational Learning Theory and Natural Learning Systems: Making learning systems practical
This is the fourth and final volume of papers from a series of workshops called "Computational Learning Theory and Ǹatural' Learning Systems." The purpose of the workshops was to explore the emerging intersection of theoretical learning research and natural learning systems. The workshops drew researchers from three historically distinct styles of learning research: computational learning theory, neural networks, and machine learning (a subfield of AI). Volume I of the series introduces the general focus of the workshops. Volume II looks at specific areas of interaction between theory and experiment. Volumes III and IV focus on key areas of learning systems that have developed recently. Vol...
Changes of Problem Representation
The purpose of our research is to enhance the efficiency of AI problem solvers by automating representation changes. We have developed a system that improves the description of input problems and selects an appropriate search algorithm for each given problem. Motivation. Researchers have accumulated much evidence on the impor tance of appropriate representations for the efficiency of AI systems. The same problem may be easy or difficult, depending on the way we describe it and on the search algorithm we use. Previous work on the automatic im provement of problem descriptions has mostly been limited to the design of individual learning algorithms. The user has traditionally been responsible f...
PRICAI 2002: Trends in Artificial Intelligence
This book constitutes the refereed proceedings of the 7th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2002, held in Tokyo, Japan in August 2002. The 57 revised full papers presented together with 5 invited contributions and 26 posters were carefully reviewed and selected from 161 submissions. The papers are organized in topical sections on logic and AI foundations, representation and reasoning of actions, constraint satisfaction, foundations of agents, foundations of learning, reinforcement learning, knowledge acquisition and management, data mining and knowledge discovery, neural network learning, learning for robots, multi-agent applications, document analysis, Web intelligence, bioinformatics, intelligent learning environments, face recognition, and multimedia and emotion.
RoboCup 2002: Robot Soccer World Cup VI
RoboCup 2002, the 6th Robot World Cup Soccer and Rescue Competitions and Conference, took place during June 19–25, 2002, at the Fukuoka Dome (main venue) in Fukuoka, Japan. It was, by far, the RoboCup event with the largestnumberofregisteredparticipants(1004persons,distributedin188teams from 29 countries) and visitors (around 120,000 persons). As was done in its previous editions since 1997, the event included several robotic competitions and aninternationalsymposium.Thepapersandposterspresentedatthesymposium constitutethemainpartofthisbook.Leaguereportsinthe?nalsectiondescribe signi?cant advances in each league and the results. The symposium organizers received 76 submissions, among which...
Advances in Neural Information Processing Systems 9
The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes neural networks and genetic algorithms, cognitive science, neuroscience and biology, computer science, AI, applied mathematics, physics, and many branches of engineering. Only about 30% of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. All of the papers presented appear in these proceedings.
Technologies for E-Services
This book constitutes the refereed preceedings of the Third International Workshop on Technologies for E-Servies, TES 2002, held in conjunction with VLDB 2002 in Hong Kong, China in August 2002. The 14 revised full papers presented together with 4 invited papers were carefully reviewed and selected. Among the topics addressed are database issues for e-services, b2b integration, model transformation, process-based application development, information fusion, information integration, business relation management, mobil servies, trust-based web security models, etc.
Brain Reflexes
Brain Reflexes
Advances in Neural Information Processing Systems 10
The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. These proceedings contain all of the papers that were presented.
Algorithmic Learning in a Random World
Algorithmic Learning in a Random World describes recent theoretical and experimental developments in building computable approximations to Kolmogorov's algorithmic notion of randomness. Based on these approximations, a new set of machine learning algorithms have been developed that can be used to make predictions and to estimate their confidence and credibility in high-dimensional spaces under the usual assumption that the data are independent and identically distributed (assumption of randomness). Another aim of this unique monograph is to outline some limits of predictions: The approach based on algorithmic theory of randomness allows for the proof of impossibility of prediction in certain situations. The book describes how several important machine learning problems, such as density estimation in high-dimensional spaces, cannot be solved if the only assumption is randomness.
