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
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.
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.
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.
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.
Multi-Agent Systems are communities of problem-solving entities that can exhibit varying degrees of intelligence. They can perceive and react to their environment, they can have individual or joint goals, for which they can plan and execute actions. Work on such systems integrates many technologies and concepts in artificial intelligence and other areas of computing as well as other disciplines. The agent paradigm has become very popular and widely used in recent years, due to its applicability to a large range of domains, from search engines to educational aids, to electronic commerce and trade, e-procurement, recommendation systems, and ambient intelligence, to cite only some. Computational logic provides a well-defined, general, and rigorous framework for studying syntax, semantics and procedures for various capabilities and functionalities of individual agents, as well as interaction amongst agents in multi-agent systems. It also provides a well-defined and rigorous framework for implementations, envir- ments, tools, and standards, and for linking together specification and verification of properties of individual agents and multi-agent systems.
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.
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.
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
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.
Transcranial electrical and magnetic stimulation techniques encompass a broad physical variety of stimuli, ranging from static magnetic fields or direct current stimulation to pulsed magnetic or alternating current stimulation with an almost infinite number of possible stimulus parameters. These techniques are continuously refined by new device developments, including coil or electrode design and flexible control of the stimulus waveforms. They allow us to influence brain function acutely and/or by inducing transient plastic after-effects in a range from minutes to days. Manipulation of stimulus parameters such as pulse shape, intensity, duration, and frequency, and location, size, and orientation of the electrodes or coils enables control of the immediate effects and after-effects. Physiological aspects such as stimulation at rest or during attention or activation may alter effects dramatically, as does neuropharmacological drug co-application. Non-linear relationships between stimulus parameters and physiological effects have to be taken into account.
The National Institute for Health and Clinical Excellence (NICE) has been regarded as a role model for the implementation of cost-effectiveness analysis (CEA), and is being closely watched by health care policy makers across the globe. This book examines Britain’s highly acclaimed approach to CEA and its international potential. It dissects the robustness of the agency’s technology appraisal processes as NICE evaluates innovative methods for diagnosis and intervention. Coverage provides a step-by-step explanation of the NICE appraisal process and examines its successes and limitations.
This in-depth introduction for students and researchers shows how to use ASP for intelligent tasks, including answering queries, planning, and diagnostics.
Because every single one of us will die, most of us would like to know what—if anything—awaits us afterward, not to mention the fate of lost loved ones. Given the nearly universal vested interest in deciding this question in favor of an afterlife, it is no surprise that the vast majority of books on the topic affirm the reality of life after death without a backward glance. But the evidence of our senses and the ever-gaining strength of scientific evidence strongly suggest otherwise. In The Myth of an Afterlife: The Case against Life after Death, Michael Martin and Keith Augustine collect a series of contributions that redress this imbalance in the literature by providing a strong, comprehensive, and up-to-date casebook of the chief arguments against an afterlife. Divided into four separate sections, this collection opens with a broad overview of the issues, as contributors consider the strongest evidence of whether or not we survive death—in particular the biological basis of all mental states and their grounding in brain activity that ceases to function at death. Next, contributors consider a host of conceptual and empirical difficulties that confront the various ways of “surviving” death—from bodiless minds to bodily resurrection to any form of posthumous survival. Then essayists turn to internal inconsistencies between traditional theological conceptions of an afterlife—heaven, hell, karmic rebirth—and widely held ethical principles central to the belief systems supporting those notions. In the final section, authors offer critical evaluations of the main types of evidence for an afterlife. Fully interdisciplinary, The Myth of an Afterlife: The Case against Life after Death brings together a variety of fields of research to make that case, including cognitiveneuroscience, philosophy of mind, personal identity, philosophy of religion, moralphilosophy, psychical research, and anomalistic psychology. As the definitive casebookof arguments against life after death, this collection is required reading for anyinstructor, researcher, and student of philosophy, religious studies, or theology. It issure to raise provocative issues new to readers, regardless of background, from thosewho believe fervently in the reality of an afterlife to those who do not or are undecidedon the matter.
Automated trading in electronic markets is one of the most common and consequential applications of autonomous software agents. Design of effective trading strategies requires thorough understanding of how market mechanisms operate, and appreciation of strategic issues that commonly manifest in trading scenarios. Drawing on research in auction theory and artificial intelligence, this book presents core principles of strategic reasoning that apply to market situations. The author illustrates trading strategy choices through examples of concrete market environments, such as eBay, as well as abstract market models defined by configurations of auctions and traders. Techniques for addressing these choices constitute essential building blocks for the design of trading strategies for rich market applications.The lecture assumes no prior background in game theory or auction theory, or artificial intelligence.Table of Contents: Introduction / Example: Bidding on eBay / Auction Fundamentals / Continuous Double Auctions / Interdependent Markets / Conclusion
In Nazi Germany, the cult of celebrity was the embodiment of Hitler’s style of cultural governance. Hitler’s rise to power owed much to the creation of his own celebrity, and the country’s greatest stars, whether they were actors, writers, or musicians, could be one of only two things. If they were compliant, they were lauded and awarded status symbols for the regime; but if they resisted—or were simply Jewish—they were traitors to be interned and murdered. This fascinating analysis offers a shocking portrait of a Hitler shaped by aspirations to Hollywood-style fame, of the correlation between art and ambition, of films used as weapons, and of sexual predilections. The Führer believed he was an artist, not a politician, and in his Germany politics and culture became one. His celebrity was cultivated and nurtured by Joseph Goebbels, Germany’s supreme head of culture. Hitler and Goebbels enjoyed the company of beautiful female film stars, and Goebbels had his own “casting couch.” In Germany’s version of Hollywood there were scandals, starlets, secret agents, premieres, and party politics. The Third Reich would launch filmmaker and actress Leni Riefenstahl to prominence by making her its own glorifying documentarian, most famously in The Triumph of the Will, the innovative propaganda film starring Hitler and widely considered to be one of the greatest movies ever made. It is no coincidence that Eva Braun, Hitler’s longtime partner and wife for the two days leading up to their joint suicide, was a photographer, and in fact shot most of the surviving photographs and film footage of her lover. This book reveals previously unpublished information about the “Hitler film,” which Goebbels envisaged as “the greatest story ever told,” although it was ultimately trumped by the dictator’s own, real-life Wagnerian finale.
Data integration is a critical problem in our increasingly interconnected but inevitably heterogeneous world. There are numerous data sources available in organizational databases and on public information systems like the World Wide Web. Not surprisingly, the sources often use different vocabularies and different data structures, being created, as they are, by different people, at different times, for different purposes. The goal of data integration is to provide programmatic and human users with integrated access to multiple, heterogeneous data sources, giving each user the illusion of a single, homogeneous database designed for his or her specific need. The good news is that, in many cases, the data integration process can be automated. This book is an introduction to the problem of data integration and a rigorous account of one of the leading approaches to solving this problem, viz., the relational logic approach. Relational logic provides a theoretical framework for discussing data integration. Moreover, in many important cases, it provides algorithms for solving the problem in a computationally practical way. In many respects, relational logic does for data integration what relational algebra did for database theory several decades ago. A companion web site provides interactive demonstrations of the algorithms. Table of Contents: Preface / Interactive Edition / Introduction / Basic Concepts / Query Folding / Query Planning / Master Schema Management / Appendix / References / Index / Author Biography Don't have access? Recommend our Synthesis Digital Library to your library or purchase a personal subscription. Email info@morganclaypool.com for details.
Transcranial magnetic stimulation (TMS) is a widely used non-invasive brain stimulation technique. It represents an exciting new frontier in neuroscience research and can be used to examine neural processes, providing insights into pathophysiology and treating a variety of neuropsychiatric illnesses. A Practical Guide to Transcranial Magnetic Stimulation Neurophysiology and Treatment Studies presents an overview of the use of TMS as both an investigational tool and as treatment for neurological and psychiatric disorders. The chapters include an overview of the history and basic principles of TMS and repetitive TMS (rTMS), the different types of TMS coils, different stimulation approaches, the use of neuronavigation, and safety considerations. The utility of single and paired TMS techniques to measure cortical inhibition, facilitation, connectivity and reactivity in motor and non-motor brain areas, the different methods of using TMS to induce brain plasticity, and use of TMS in cognitive studies are explored. It also covers TMS and rTMS combined with electroencephalography (EEG) in neurophysiological studies. The authors provide a summary of the clinical applications of TMS in neurological and psychiatric disorders including depression, schizophrenia, stroke, Parkinson disease, and pain. This up-to-date volume provides a compendious review of the use of TMS and rTMS that will help guide the utility of this methodology in both clinical and research settings. This practical guide will be a useful resource for those new to the field, as well as experienced users, for both research and clinical settings.
Cooperative game theory is a branch of (micro-)economics that studies the behavior of self-interested agents in strategic settings where binding agreements among agents are possible. Our aim in this book is to present a survey of work on the computational aspects of cooperative game theory. We begin by formally defining transferable utility games in characteristic function form, and introducing key solution concepts such as the core and the Shapley value. We then discuss two major issues that arise when considering such games from a computational perspective: identifying compact representations for games, and the closely related problem of efficiently computing solution concepts for games. We survey several formalisms for cooperative games that have been proposed in the literature, including, for example, cooperative games defined on networks, as well as general compact representation schemes such as MC-nets and skill games. As a detailed case study, we consider weighted voting games: a widely-used and practically important class of cooperative games that inherently have a natural compact representation. We investigate the complexity of solution concepts for such games, and generalizations of them. We briefly discuss games with non-transferable utility and partition function games. We then overview algorithms for identifying welfare-maximizing coalition structures and methods used by rational agents to form coalitions (even under uncertainty), including bargaining algorithms. We conclude by considering some developing topics, applications, and future research directions.
Automated trading in electronic markets is one of the most common and consequential applications of autonomous software agents. Design of effective trading strategies requires thorough understanding of how market mechanisms operate, and appreciation of strategic issues that commonly manifest in trading scenarios. Drawing on research in auction theory and artificial intelligence, this book presents core principles of strategic reasoning that apply to market situations. The author illustrates trading strategy choices through examples of concrete market environments, such as eBay, as well as abstract market models defined by configurations of auctions and traders. Techniques for addressing these choices constitute essential building blocks for the design of trading strategies for rich market applications. The lecture assumes no prior background in game theory or auction theory, or artificial intelligence. Table of Contents: Introduction / Example: Bidding on eBay / Auction Fundamentals / Continuous Double Auctions / Interdependent Markets / Conclusion
Logic Programming is a style of programming in which programs take the form of sets of sentences in the language of Symbolic Logic. Over the years, there has been growing interest in Logic Programming due to applications in deductive databases, automated worksheets, Enterprise Management (business rules), Computational Law, and General Game Playing. This book introduces Logic Programming theory, current technology, and popular applications. In this volume, we take an innovative, model-theoretic approach to logic programming. We begin with the fundamental notion of datasets, i.e., sets of ground atoms. Given this fundamental notion, we introduce views, i.e., virtual relations; and we define classical logic programs as sets of view definitions, written using traditional Prolog-like notation but with semantics given in terms of datasets rather than implementation. We then introduce actions, i.e., additions and deletions of ground atoms; and we define dynamic logic programs as sets of action definitions. In addition to the printed book, there is an online version of the text with an interpreter and a compiler for the language used in the text and an integrated development environment for use in developing and deploying practical logic programs.
The German health care system is on a collision course with budget realities. Costs are high and rising, and quality problems are becoming ever more apparent. Decades of reforms have produced little change to these troubling trends. Why has Germany failed to solve these cost and quality problems? The reason is that Germany has not set value for patients as the overarching goal, defined as the patient health outcomes achieved per euro expended. This book lays out an action agenda to move Germany to a high value system: care must be reorganized around patients and their medical conditions, providers must compete around the outcomes they achieve, health plans must take an active role in improving subscriber health, and payment must shift to models that reward excellent providers. Also, private insurance must be integrated in the risk-pooling system. These steps are practical and achievable, as numerous examples in the book demonstrate. Moving to a value-based health care system is the only way for Germany to continue to ensure access to excellent health care for everyone.
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