Recently, the ICT field has seen a shift from machine centered focuses to human and user knowledge-based approaches. However, as the priorities shift, questions arise on how to detect and monitor users' behaviour. Human Behavior Recognition Technologies: Intelligent Applications for Monitoring and Security addresses these questions and more as it takes an insightful glance into the applications and dependability of behaviour detection. In addition, this comprehensive publication looks into the social, ethical, and legal implications of these areas. Researchers and practitioners interested in the computational aspects of behaviour monitoring as well as the ethical and legal implications will find this reference source beneficial.

The Pacific Rim International Conference on Artificial Intelligence (PRICAI) is a biennial international event which focuses on Artificial Intelligence (AI) theories and technologies, and their applications which are of social and economic importance for countries in the Pacific Rim region. Seven earlier conferences were held in: Nagoya, Japan (1990); Seoul, Korea (1992); Beijing, China (1994); Cairns, Australia (1996); Singapore (1998); Melbourne, Australia (2000); and Tokyo, Japan (2002). PRICAI 2004 was the eigth in the series and was held in Auckland, New Zealand in August 2004. PRICAI 2004 had attracted a historical record number of submissions, a total of 356 papers. After careful reviews by at least two international Program Committee members or referees, 94 papers were accepted as full papers (27%) and 54 papers (15%) were accepted as posters. Authors of accepted papers came from 27 countries. This volume of the proceedings contains all the 94 full papers but only a 2-page - tended abstract of each of the accepted posters. The full papers were categorized into four sections, namely: AI foundations, computational intelligence, AI technologies and systems, and AI specific application areas. Among the papers submitted, we found "Agent Technology" to be the area having the most papers submitted. This was followed by "Evolutionary Computing", "Computational Learning", and "Image Processing".

Much of AI research is about problem-solving strategies, and several techniques have been crystalized. One such technique is constraint satisfaction or reasoning based on relations. Constraint-based reasoning is used to solve a wide field of problems, and recently constraint techniques have been incorporated into logic programming languages, yielding a whole new field of research and application: constraint logic programming. Constraint satisfaction techniques have become part of almost all introductory books on AI. This monograph is about constraint satisfaction. It differs from others in that it presents all approaches under a common, generalizing view: dynamic constraints. This new way of viewing constraints provides new insights about the different approaches, and forms a very practical basis for teaching constraint-based reasoning. A uniform view of the constraint world is also a good basis for constraint research. This text is not intended to be a self-contained textbook on constraint-based reasoning, but rather a coherent text on an interesting view of the field.