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Theory of Computation

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Logic-based formalizations of argumentation, which assume a set of formulae and then lay out arguments and counterarguments that can be obtained from these formulae, have been refined in recent years in an attempt to capture more closely real-world practical argumentation. In Elements of Argumentation, Philippe Besnard and Anthony Hunter introduce techniques for formalizing deductive argumentation in artificial intelligence, emphasizing emerging formalizations for practical argumentation.

The minimum description length (MDL) principle is a powerful method of inductive inference, the basis of statistical modeling, pattern recognition, and machine learning. It holds that the best explanation, given a limited set of observed data, is the one that permits the greatest compression of the data.

Randomization is an important tool in the design of algorithms, and the ability of randomization to provide enhanced power is a major research topic in complexity theory.

A System for Representing and Using Real-World Knowledge

"Consider for a moment the layers of structure and meaning that are attached to concepts like lawsuit, birthday party, fire, mother, walrus, cabbage, or king.... If I tell you that a house burned down, and that the fire started at a child's birthday party, you will think immediately of the candles on the cake and perhaps of the many paper decorations. You will not, In all probability, find yourself thinking about playing pin-the- tall-on-the-donkey or about the color of the cake's icing or about the fact that birthdays come once a year.

Investigating meta-programming within the logic programming paradigm, Meta-Logics and Logic Programming presents original research on an important extension of logic programming that makes it more amenable for knowledge representation and programming in general. The 12 contributions, many written especially for this book, explore the foundations, language design issues, and applications of meta-programming in logic programming.

Although state variable concepts are a part of modern control theory, they have not been extensively applied in communication theory. The purpose of this book is to demonstrate how the concepts and methods of state variables can be used advantageously in analyzing a variety of communication theory problems.

There is increasing interest in genetic programming by both researchers and professional software developers. These twenty-two invited contributions show how a wide variety of problems across disciplines can be solved using this new paradigm.

New Directions

Classical computationalism—-the view that mental states are computational states—-has come under attack in recent years. Critics claim that in defining computation solely in abstract, syntactic terms, computationalism neglects the real-time, embodied, real-world constraints with which cognitive systems must cope.

Too often, designers of computer systems, both hardware and software, use models and concepts that focus on the artifact while ignoring the context in which the artifact will be used. According to this book, that assumption is a major reason for many of the failures in contemporary computer systems development.

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