Not only too much, but too little emotion can impair decision making. According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions.Part 1 of this book provides the intellectual framework for affective computing. It includes background on human emotions, requirements for emotionally intelligent computers, applications of affective computing, and moral and social questions raised by the technology. Part 2 discusses the design and construction of affective computers. Although this material is more technical than that in Part 1, the author has kept it less technical than typical scientific publications in order to make it accessible to newcomers. Topics in Part 2 include signal-based representations of emotions, human affect recognition as a pattern recognition and learning problem, recent and ongoing efforts to build models of emotion for synthesizing emotions in computers, and the new application area of affective wearable computers.

    The first part of the book is devoted to finite automata and their properties. Pushdown automata provide a broader class of models and enable the analysis of context-free languages. In the remaining chapters, Turing machines are introduced and the book culminates in analyses of effective computability, decidability, and G�del's incompleteness theorems. Students who already have some experience with elementary discrete mathematics will find this a well-paced first course, and a number of supplementary chapters introduce more advanced concepts.

    I'm delighted to have the oppor- nity to update and expand the book. The ?rst edition ended on a sad note and that was re?ected in the writing. It is now eleven years later and the project has come to a satisfying conclusion. Since its inception, the checkers project has consumed eighteen years of my life-- twenty if you count the pre-CHINOOK and post-solving work. It's hard for me to believe that I actually stuck with it for that long. My wife, Steph, would probably have something witty to say about my obsessive behavior. Rereading the book after a decade was dif?cult for me. When I originally wrote One Jump Ahead, I vowed to be candid in my telling of the story. That meant being honest about what went right and what went wrong. I have been criticized for being hard on some of the characters. That may be so, but I hope everyone will agree that the person receiving the most criticism was, justi?ably, me. I tried to be balanced in the storytelling, re?ecting things as they really happened and not as some sanitized everyone-lived-happily-ever-after tale.

    Unlike traditional empirical psychology, it is more oriented toward the how than the what. An experiment in mind design is more likely to be an attempt to build something and make it work--as in artificial intelligence--than to observe or analyze what already exists. Mind design is psychology by reverse engineering.When Mind Design was first published in 1981, it became a classic in the then-nascent fields of cognitive science and AI. This second edition retains four landmark essays from the first, adding to them one earlier milestone (Turing's Computing Machinery and Intelligence) and eleven more recent articles about connectionism, dynamical systems, and symbolic versus nonsymbolic models. The contributors are divided about evenly between philosophers and scientists. Yet all are philosophical in that they address fundamental issues and concepts; and all are scientific in that they are technically sophisticated and concerned with concrete empirical research.ContributorsRodney A. Brooks, Paul M. Churchland, Andy Clark, Daniel C. Dennett, Hubert L. Dreyfus, Jerry A. Fodor, Joseph Garon, John Haugeland, Marvin Minsky, Allen Newell, Zenon W. Pylyshyn, William Ramsey, Jay F. Rosenberg, David E. Rumelhart, John R. Searle, Herbert A. Simon, Paul Smolensky, Stephen Stich, A.M. Turing, Timothy van Gelder

    It describes the different commercial agents currently in use, strategic benefits, and integrating agents into existing systems. The authors use real case studies to show how to successfully deploy agents for specific business purposes.

    The desolate and hopeless future mimics that of the Terminator film series, except that the humans are caught in the conflict between the machines themselves.

    Through close attention to the metaphors of AI and their consequences for the field's patterns of success and failure, it argues for a reorientation of the field away from thought in the head and toward activity in the world. By considering computational ideas in a philosophical framework, the author eases critical dialogue between technology and the humanities and social sciences. AI can benefit from new understandings of human nature, and in return, it offers a powerful mode of investigation into the practicalities and consequences of physical realization.