The creation of intelligent robots is surely one of the most exciting and ch- lenginggoals of Arti?cial Intelligence. A robot is, ?rst of all, nothing but an inanimate machine with motors and sensors. In order to bring life to it, the machine needs to be programmed so as to make active use of its hardware c- ponents. This turns a machine into an autonomous robot. Since about the mid nineties of the past century, robot programming has made impressive progress. State-of-the-art robots are able to orient themselves and move around freely in indoor environments or negotiate di?cult outdoor terrains, they can use stereo vision to recognize objects, and they are capable of simple object manipulation with the help of arti?cial extremities. At a time where robots perform these tasks more and more reliably, weare ready to pursue the next big step, which is to turn autonomous machines into reasoning robots.Areasoning robot exhibits higher cognitive capabilities like following complex and long-term strategies, making rational decisions on a high level, drawing logical conclusions from sensor information acquired over time, devising suitable plans, and reacting sensibly in unexpected situations. All of these capabilities are characteristics of human-like intelligence and ultimately distinguish truly intelligent robots from mere autonomous machines

This book constitutes the refereed proceedings of the 5th Computer Games Workshop, CGW 2016, and the 5th Workshop on General Intelligence in Game-Playing Agents, GIGA 2016, held in conjunction with the 25th International Conference on Artificial Intelligence, IJCAI 2016, in New York, USA, in July 2016.The 12 revised full papers presented were carefully reviewed and selected from 25 submissions. The papers address all aspects of artificial intelligence and computer game playing. They discuss topics such as Monte-Carlo methods; heuristic search; board games; card games; video games; perfect and imperfect information games; puzzles and single player games; multi-player games; combinatorial game theory; applications; computational creativity; computational game theory; evaluation and analysis; game design; knowledge representation; machine learning; multi-agent systems; opponent modeling; planning.

This book constitutes the refereed proceedings of the Fourth Computer Games Workshop, CGW 2015, and the Fourth Workshop on General Intelligence in Game-Playing Agents, GIGA 2015, held in conjunction with the 24th International Conference on Artificial Intelligence, IJCAI 2015, Buenos Aires, Argentina, in July 2015.The 12 revised full papers presented were carefully reviewed and selected from 27 submissions. The papers address all aspects of artificial intelligence and computer game playing. They discuss topics such as Monte-Carlo methods; heuristic search; board games; card games; video games; perfect and imperfect information games; puzzles and single player games; multi-player games; combinatorial game theory; applications; computational creativity; computational game theory; evaluation and analysis; game design; knowledge representation; machine learning; multi-agent systems; opponent modeling; planning; reasoning; search.

This book constitutes the refereed proceedings of the 37th Annual German Conference on Artificial Intelligence, KI 2014, held in Stuttgart, Germany, in September 2014. The 24 revised full papers presented together with 7 short papers were carefully reviewed and selected from 62 submissions. The papers are organized in thematic topics on cognitive modeling, computer vision, constraint satisfaction, search, and optimization, knowledge representation and reasoning, machine learning and data mining, planning and scheduling.

General game players are computer systems able to play strategy games based solely on formal game descriptions supplied at "runtime" (n other words, they don't know the rules until the game starts). Unlike specialized game players, such as Deep Blue, general game players cannot rely on algorithms designed in advance for specific games; they must discover such algorithms themselves. General game playing expertise depends on intelligence on the part of the game player and not just intelligence of the programmer of the game player. GGP is an interesting application in its own right. It is intellectually engaging and more than a little fun. But it is much more than that. It provides a theoretical framework for modeling discrete dynamic systems and defining rationality in a way that takes into account problem representation and complexities like incompleteness of information and resource bounds. It has practical applications in areas where these features are important, e.g., in business and law. More fundamentally, it raises questions about the nature of intelligence and serves as a laboratory in which to evaluate competing approaches to artificial intelligence. This book is an elementary introduction to General Game Playing (GGP). (1) It presents the theory of General Game Playing and leading GGP technologies. (2) It shows how to create GGP programs capable of competing against other programs and humans. (3) It offers a glimpse of some of the real-world applications of General Game Playing.

This book constitutes the refereed proceedings of the 25th Australasian Joint Conference on Artificial Intelligence, AI 2012, held in Sydney, Australia, in December 2012. The 76 revised full papers presented were carefully reviewed and selected from 196 submissions. The papers address a wide range of agents, applications, computer vision, constraints and search, game playing, information retrieval, knowledge representation, machine learning, planning and scheduling, robotics and uncertainty in AI.

The creation of intelligent robots is surely one of the most exciting and ch- lenginggoals of Arti?cial Intelligence. A robot is, ?rst of all, nothing but an inanimate machine with motors and sensors. In order to bring life to it, the machine needs to be programmed so as to make active use of its hardware c- ponents. This turns a machine into an autonomous robot. Since about the mid nineties of the past century, robot programming has made impressive progress. State-of-the-art robots are able to orient themselves and move around freely in indoor environments or negotiate di?cult outdoor terrains, they can use stereo vision to recognize objects, and they are capable of simple object manipulation with the help of arti?cial extremities. At a time where robots perform these tasks more and more reliably, weare ready to pursue the next big step, which is to turn autonomous machines into reasoning robots.Areasoning robot exhibits higher cognitive capabilities like following complex and long-term strategies, making rational decisions on a high level, drawing logical conclusions from sensor information acquired over time, devising suitable plans, and reacting sensibly in unexpected situations. All of these capabilities are characteristics of human-like intelligence and ultimately distinguish truly intelligent robots from mere autonomous machines

This book constitutes the thoroughly refereed and revised proceedings of the 9th International Workshop on Computational Logic for Multi-Agent Systems, CLIMA IX, held in Dresden, Germany, in September 2008 and co-located with the 11th European Conference on Logics in Artificial Intelligence, JELIA 2008.

The 8 full papers, presented together with two invited papers, were carefull selected from 18 submissions and passed through two rounds of reviewing and revision. Topics addressed in the regular papers include the use of automata-based techniques for verifying agents' conformance with protocols, and an approach based on the C+ action description language to provide formal specifications of social processes such as those used in business processes and social networks. Other topics include casting reasoning as planning and thus providing an analysis of reasoning with resource bounds, a discussion of the formal properties of Computational Tree Logic (CTL) extended with knowledge operators, and the use of argumentation in multi-agent negotiation. The invited contributions discuss complexity results for model-checking temporal and strategic properties of multi-agent systems, and the challenges in design and development of programming languages for multi-agent systems.

Artificial systems that think and behave intelligently are one of the most exciting and challenging goals of Artificial Intelligence. Action Programming is the art and science of devising high-level control strategies for autonomous systems which employ a mental model of their environment and which reason about their actions as a means to achieve their goals. Applications of this programming paradigm include autonomous software agents, mobile robots with high-level reasoning capabilities, and General Game Playing. These lecture notes give an in-depth introduction to the current state-of-the-art in action programming. The main topics are knowledge representation for actions, procedural action programming, planning, agent logic programs, and reactive, behavior-based agents. The only prerequisite for understanding the material in these lecture notes is some general programming experience and basic knowledge of classical first-order logic. Table of Contents: Introduction / Mathematical Preliminaries / Procedural Action Programs / Action Programs and Planning / Declarative Action Programs / Reactive Action Programs / Suggested Further Reading

A logic-based approach to the design of computing systems would, undoubtedly, offer many advantages over the imperative paradigm most commonly applied so far for programming and hardware design and, consequently, logic, again and again, has been heralded as the basis for the next generation of computer systems. While logic and formal methods are indeed gaining ground in many areas of computer science and artificial intelligence the expected revolution has not yet happened. In this book the author offers a convincing solution to the ramification problem and qualification problem associated with the frame problem and thus contributes to a satisfactory solution of the core problem and related challenges. Thielscher bases his approach on the fluent calculus, a first-order Prolog-like formalism allowing for the description of actions and change.

Inhalt: Ingrid Biehl, Copyright-Schutz digitaler Daten durch kryptographische Fingerprinting-Schemata: Kryptographische Zeichen - Die Fingerprinting-Modelle - Ein assymetrisches Fingerprinting-Schema - Ein anonymes Fingerprinting-Schema Michael Thielscher, Kognitive Robotik - Perspektiven und Grenzen der KI-Forschung: Ein neuartiges Werkzeug - Kognitive Fahigkeiten bei Robotern - Perspektiven und Grenzen der "kunstlichen Intelligenz"-Forschung . (Franz Steiner 1999)