Nowadays, intelligent techniques are more and more used in Computer Graphics in order to optimise the processing time, to find more accurate solutions for a lot of Computer Graphics problems, than with traditional methods, or simply to find solutions in problems where traditional methods fail. The purpose of this volume is to present current work of the Intelligent Computer Graphics community, a community growing up year after year. This volume is a kind of continuation of the previously published Springer volumes “Artificial Intelligence Techniques for Computer Graphics” (2008) and “Intelligent Computer Graphics 2009” (2009). This volume contains selected extended papers from the last 3IA Conference (3IA’2010), which has been held in Athens (Greece) in May 2010. This year papers are particularly exciting and concern areas like rendering, viewpoint quality, data visualisation, vision, computational aesthetics, scene understanding, intelligent lighting, declarative modelling, GIS, scene reconstruction and other important themes.

In Computer Graphics, the use of intelligent techniques started more recently than in other research areas. However, during these last two decades, the use of intelligent Computer Graphics techniques is growing up year after year and more and more interesting techniques are presented in this area. The purpose of this volume is to present current work of the Intelligent Computer Graphics community, a community growing up year after year. This volume is a kind of continuation of the previously published Springer volumes “Artificial Intelligence Techniques for Computer Graphics” (2008), “Intelligent Computer Graphics 2009” (2009) and “Intelligent Computer Graphics 2010” (2010). This volume contains selected extended papers from the last 3IA Conference (3IA’2011), which has been held in Athens (Greece) in May 2011. This year papers are particularly exciting and concern areas like virtual reality, artificial life, data visualization, games, global illumination, point cloud modelling, declarative modelling, scene reconstruction and many other very important themes.

In Computer Graphics, the use of intelligent techniques started more recently than in other research areas. However, during these last two decades, the use of intelligent Computer Graphics techniques is growing up year after year and more and more interesting techniques are presented in this area. The purpose of this volume is to present current work of the Intelligent Computer Graphics community, a community growing up year after year. This volume is a kind of continuation of the previously published Springer volumes “Artificial Intelligence Techniques for Computer Graphics” (2008), “Intelligent Computer Graphics 2009” (2009), “Intelligent Computer Graphics 2010” (2010) and “Intelligent Computer Graphics 2011” (2011). Usually, this kind of volume contains, every year, selected extended papers from the corresponding 3IA Conference of the year. However, the current volume is made from directly reviewed and selected papers, submitted for publication in the volume “Intelligent Computer Graphics 2012”. This year papers are particularly exciting and concern areas like plant modelling, text-to-scene systems, information visualization, computer-aided geometric design, artificial life, computer games, realistic rendering and many other very important themes.

Context-aware ranking is an important task with many applications. E.g. in recommender systems items (products, movies, ...) and for search engines webpages should be ranked. In all these applications, the ranking is not global (i.e. always the same) but depends on the context. Simple examples for context are the user for recommender systems and the query for search engines. More complicated context includes time, last actions, etc. The major problem is that typically the variable domains (e.g. customers, products) are categorical and huge, the observations are very sparse and only positive events are observed. In this book, a generic method for context-aware ranking as well as its application are presented. For modelling a new factorization based on pairwise interactions is proposed and compared to other tensor factorization approaches. For learning, the `Bayesian Context-aware Ranking' framework consisting of an optimization criterion and algorithm is developed. The second main part of the book applies this general theory to the three scenarios of item, tag and sequential-set recommendation. Furthermore extensions of time-variant factors and one-class problems are studied. This book generalizes and builds on work that has received the `WWW 2010 Best Paper Award', the `WSDM 2010 Best Student Paper Award' and the `ECML/PKDD 2009 Best Discovery Challenge Award'.

Multi-Agent System (MAS) is an exciting, emerging paradigm expected to play a key role in many society-changing practices. The International Conference on Principles and Practice of Multi-Agent Systems (PRIMA) is a leading scientific conference for research on intelligent agent systems and multi-agent systems, attracting high quality, state-of-the-art research from all over the world. PRIMA’09 was the 12th in the series of PRIMA conferences and was held in Nagoya, Japan. Beside a single-track main conference, PRIMA’09 also included a number of workshops which were designed to provide a forum for researchers and practitioners to present and exchange the latest developments at the MAS frontier. This book constitutes the post-proceedings of workshops under PRIMA’09. Readers will be able to explore a diverse range of topics and detailed discussions related to a number of important themes in our ever changing world. This collection plays an important role in bridging the gap between MAS theory and practice. It emphasizes the importance of MAS in the research and development of smart power grid systems, decision support systems, optimization and analysis systems for road traffic and markets, environmental monitoring and simulation, and in many other real-world applications and publicizes and extends MAS technology to many domains in this fast moving information age.

Humans engage in a seemingly endless variety of different behaviors, of which some are found across species, while others are conceived of as typically human. Most generally, behavior comes about through the interplay of various constraints – informational, mechanical, neural, metabolic, and so on – operating at multiple scales in space and time. Over the years, consensus has grown in the research community that, rather than investigating behavior only from bottom up, it may be also well understood in terms of concepts and laws on the phenomenological level. Such top down approach is rooted in theories of synergetics and self-organization using tools from nonlinear dynamics. The present compendium brings together scientists from all over the world that have contributed to the development of their respective fields departing from this background. It provides an introduction to deterministic as well as stochastic dynamical systems and contains applications to motor control and coordination, visual perception and illusion, as well as auditory perception in the context of speech and music.

Computational Methods for the Innovative Design of Electrical Devices is entirely focused on the optimal design of various classes of electrical devices. Emerging new methods, like e.g. those based on genetic algorithms, are presented and applied in the design optimization of different devices and systems. Accordingly, the solution to field analysis problems is based on the use of finite element method, and analytical methods as well. An original aspect of the book is the broad spectrum of applications in the area of electrical engineering, especially electrical machines. This way, traditional design criteria of conventional devices are revisited in a critical way, and some innovative solutions are suggested. In particular, the optimization procedures developed are oriented to three main aspects: shape design, material properties identification, machine optimal behaviour. Topics covered include: • New parallel finite-element solvers • Response surface method • Evolutionary computing • Multiobjective optimization • Swarm intelligence • MEMS applications • Identification of magnetic properties of anisotropic laminations • Neural networks for non-destructive testing • Brushless DC motors, transformers • Permanent magnet disc motors, magnetic separators • Magnetic levitation systems