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Information Security and Privacy
This book constitutes the refereed proceedings of the 5th Australasian Conference on Information Security and Privacy, ACISP 2000, held in Brisbane, QLD, Australia, in July 2000. The 37 revised full papers presented together with two invited contributions were carefully reviewed and selected from a total of 81 submissions. The book offers topical sections on network security, public key cryptography, cryptographic implementation issues, electronic commerce, key recovery, public key infrastructure, Boolean functions, intrusion detection, codes, digital signatures, secret sharing, and protocols.
Component-Based Software Engineering
This book constitutes the refereed proceedings of the 7th International Symposium on Component-Based Software Engineering, CBSE 2004, held in Edinburgh, UK in May 2004 as an adjunct event to ICSE 2004. The 12 revised long papers and 13 revised short papers presented together with the abstracts of 2 invited talks were carefully reviewed and selected from 82 submissions. The papers are organized in topical sections on generation and adoptation of component-based systems, tools and building frameworks, components for real-time embedded systems, extra-functional properties of components and component-based systems, and measurement and prediction models for component assemblies.
Plan-Based Control of Robotic Agents
Robotic agents, such as autonomous office couriers or robot tourguides, must be both reliable and efficient. Thus, they have to flexibly interleave their tasks, exploit opportunities, quickly plan their course of action, and, if necessary, revise their intended activities. This book makes three major contributions to improving the capabilities of robotic agents: - first, a plan representation method is introduced which allows for specifying flexible and reliable behavior - second, probabilistic hybrid action models are presented as a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans - third, the system XFRMLEARN capable of learning structured symbolic navigation plans is described in detail.
Multiobjective Heuristic Search
Solutions to most real-world optimization problems involve a trade-off between multiple conflicting and non-commensurate objectives. Some of the most challenging ones are area-delay trade-off in VLSI synthesis and design space exploration, time-space trade-off in computation, and multi-strategy games. Conventional search techniques are not equipped to handle the partial order state spaces of multiobjective problems since they inherently assume a single scalar objective function. Multiobjective heuristic search techniques have been developed to specifically address multicriteria combinatorial optimization problems. This text describes the multiobjective search model and develops the theoretic...
Interoperating Geographic Information Systems
Geographic information systems have developed rapidly in the past decade, and are now a major class of software, with applications that include infrastructure maintenance, resource management, agriculture, Earth science, and planning. But a lack of standards has led to a general inability for one GIS to interoperate with another. It is difficult for one GIS to share data with another, or for people trained on one system to adapt easily to the commands and user interface of another. Failure to interoperate is a problem at many levels, ranging from the purely technical to the semantic and the institutional. Interoperating Geographic Information Systems is about efforts to improve the ability o...
Scientific Engineering for Distributed Java Applications
This book constitutes the thoroughly refereed postproceedings of the International Workshop on Scientific Engineering for Distributed Java Applications, FIDJI 2002, held in Luxembourg-Kirchberg, Luxembourg in November 2002. The 16 revised full papers presented together with a keynote paper and 3 abstracts were carefully selected from 33 submissions during two rounds of reviewing and improvement. Among the topics addressed are Java coordination, Web service architectures, transaction models, CORBA-based distributed systems, mobile objects, Java group toolkits, distributed process management systems, active objects in J2EE, Java frameworks, Jini, component-based distributed applications, Java middleware, fault-tolerant mobile systems.
Logic Programming
Includes tutorials, invited lectures, and refereed papers on all aspects of logic programming including: Constraints, Concurrency and Parallelism, Deductive Databases, Implementations, Meta and Higher-order Programming, Theory, and Semantic Analysis. September 2-6, 1996, Bonn, Germany Every four years, the two major international scientific conferences on logic programming merge in one joint event. JICSLP'96 is the thirteenth in the two series of annual conferences sponsored by The Association for Logic Programming. It includes tutorials, invited lectures, and refereed papers on all aspects of logic programming including: Constraints, Concurrency and Parallelism, Deductive Databases, Implementations, Meta and Higher-order Programming, Theory, and Semantic Analysis. The contributors are international, with strong contingents from the United States, United Kingdom, France, and Japan. Logic Programming series, Research Reports and Notes
The Quest for Artificial Intelligence
Artificial intelligence (AI) is a field within computer science that is attempting to build enhanced intelligence into computer systems. This book traces the history of the subject, from the early dreams of eighteenth-century (and earlier) pioneers to the more successful work of today's AI engineers. AI is becoming more and more a part of everyone's life. The technology is already embedded in face-recognizing cameras, speech-recognition software, Internet search engines, and health-care robots, among other applications. The book's many diagrams and easy-to-understand descriptions of AI programs will help the casual reader gain an understanding of how these and other AI systems actually work. Its thorough (but unobtrusive) end-of-chapter notes containing citations to important source materials will be of great use to AI scholars and researchers. This book promises to be the definitive history of a field that has captivated the imaginations of scientists, philosophers, and writers for centuries.
Integrity and Internal Control in Information Systems V
Integrity and Internal Control in Information Systems V represents a continuation of the dialogue between researchers, information security specialists, internal control specialists and the business community. The objectives of this dialogue are: -To present methods and techniques that will help business achieve the desired level of integrity in information systems and data; -To present the results of research that may be used in the near future to increase the level of integrity or help management maintain the desired level of integrity; -To investigate the shortcomings in the technologies presently in use, shortcomings that require attention in order to protect the integrity of systems in general. The book contains a collection of papers from the Fifth International Working Conference on Integrity and Internal Control in Information Systems (IICIS), sponsored by the International Federation for Information Processing (IFIP) and held in Bonn, Germany in November 2002.
Planning with Markov Decision Processes
Markov Decision Processes (MDPs) are widely popular in Artificial Intelligence for modeling sequential decision-making scenarios with probabilistic dynamics. They are the framework of choice when designing an intelligent agent that needs to act for long periods of time in an environment where its actions could have uncertain outcomes. MDPs are actively researched in two related subareas of AI, probabilistic planning and reinforcement learning. Probabilistic planning assumes known models for the agent's goals and domain dynamics, and focuses on determining how the agent should behave to achieve its objectives. On the other hand, reinforcement learning additionally learns these models based on...
