The Ninth Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE) was held October 14–18, 2013, at Northeastern University in Boston, Massachusetts. The mission of the AIIDE conference is to provide a forum for researchers and game developers to discuss ways that AI can enhance games and other forms of interactive entertainment. In addition to presentations on adapting standard AI techniques such as search, planning and machine learning for use within games, key topic areas include creating realistic autonomous characters, interactive narrative, procedural content generation, and integrating AI into game design and production tools.

Thailand, a country of 65 million people, has had an active AI community for almost three decades. Research on Thai language processing and expert systems was then concentrated on at the laboratory. King Mongkut's University of Technology Thonburi also set up its own AI center -- as a The guest editor for this column was loosely affiliated group. Yuen Poovarawan was the pioneer in computer language processing of the Thai language. It is the National Electronics and Computer Technology now expanded to the Center of Excellence, supported Center (NECTEC) put together research development by National Electronics and Computer plans in AIrelated fields, for example, natural Technology Center (NECTEC), and focuses on language processing, expert systems, and merging together two types of technology: knowledge intelligent image processing.

The preliminary Call for Papers, including an The IAAI-14 technical program will feature overview of the special tracks and a preview of talks on seven award-winning deployed AI planned innovations is available at www.aaai.

Have you ever been surprised by poor class performance on a midterm question, and wondered why you were met with silence each time you asked “Any questions?” during the lecture on that topic? Do your students sometimes feel like they understood everything that was said in lecture, only to go home, start the homework, and immediately get stuck? Do you find that you only really learn something when you have to explain it to others? Peer instruction is an active learning pedagogy that addresses these challenges and opportunities

In order to emphasize the importance of implemented systems for the field, we also called for system demonstrations; 7 were accepted for the conference, 1 of them associated with a research abstract and 6 of them described in a demonstration extended abstract. At this edition of ICAIL, the Donald H. Berman best student paper award was won by Tran Thi Oanh (Japan Advanced Institute of Science and Technology; JAIST) for the paper entitled "Reference Resolution in Legal Texts" that she wrote with Minh Le Nguyen and Akira Shimazu. Traditionally, ICAIL hosts a lively and varied program of tutorials and workshops. At this conference, there were tutorials covering an introduction to artificial intelligence and law, web ontology and data design, LegalRuleML, and textual information extraction. There were workshops on argumentation, coherence, open and smart data, evidence, e-discovery, e-justice, and network analysis. Also, the international workshop series, Computational Models of Natural Argument, joined ICAIL for its 13th edition (CMNA XIII). The conference was held under the auspices of the Senate of the Italian Republic with as hosting institution the Consiglio Nazionale delle Ricerche (National Research Council of Italy), central unit in Rome. Both AAAI and ACM SIGART were in cooperation. Conference officials were Bart Verheij (program chair), Enrico Francesconi (conference chair), and Anne Gardner (secretary/treasurer).

Rinke Hoekstra (VU University from transferring and adapting semantic web Amsterdam) presented linked open data tools technologies to the big data quest. Finally, in the Social to discover connections within established scientific Networks and Social Contagion symposium, a data sets. Louiqa Rashid (University of Maryland) community of researchers explored topics such as social presented work on similarity metrics linking together contagion, game theory, network modeling, network-based drugs, genes, and diseases. Kyle Ambert (Intel) presented inference, human data elicitation, and Finna, a text-mining system to identify passages web analytics. Highlights of the symposia are contained of interest containing descriptions of neuronal in this report.

The workshop was accompanied by an evening Games are unique in that their components event, DAGGER, which drew together local game developers (from the rules and goals of the game to the appearance and academic research projects. Acting both of avatars and their dialogue) must encompass as an exhibition and as an informal gathering, the both functional and aesthetic prerequisites. Artificial DAGGER event allowed attendees to interact directly intelligence usually focuses on the functional quality with a wide variety of game types and technologies, of such game components, for example, ensuring as well as with their developers. As events such that an avatar can traverse a level in minimal time or as DAGGER help bridge the gap between theoretical that AI can win over any human in a strategy game. The papers avatar, or level would appeal to a particular player. of the workshop were published as AAAI Technical The Workshop on AI and Game Aesthetics provided Report WS-13-19.

Many problems in computational sustainability require making a sequence of decisions in complex, uncertain environments. Such problems are generally notoriously difficult. In this article, we review the recently discovered notion of adaptive submodularity, an intuitive diminishing returns condition that generalizes the classical notion of submodular set functions to sequential decision problems. Problems exhibiting the adaptive submodularity property can be efficiently and provably near-optimally solved using simple myopic policies. We illustrate this concept in several case studies of interest in computational sustainability: First, we demonstrate how it can be used to efficiently plan for resolving uncertainty in adaptive management scenarios. Secondly, we show how it applies to dynamic conservation planning for protecting endangered species, a case study carried out in collaboration with the US Geological Survey and the US Fish and Wildlife Service.

Therefore, diagnostic algorithms must reason backwards from symptoms to causes. For example, determining that a dead battery is the cause of your car not starting in the morning (and not the wiring or the ignition switch). The domains of diagnostic algorithms includes analog and digital circuits, software systems, thermal systems, biological systems, and physical mechanisms. The same classes of diagnostic algorithms can apply in all domains. Diagnostic algorithms make observations, often in real time, of a system being diagnosed.

Computational sustainability problems, which exist in dynamic environments with high amounts of uncertainty, provide a variety of unique challenges to artificial intelligence research and the opportunity for significant impact upon our collective future. This editorial provides an overview of artificial intelligence for computational sustainability, and introduces this special issue of AI Magazine.