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Plucked
  • Language: en
  • Pages: 296

Plucked

  • Type: Book
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  • Published: 2016-11
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  • Publisher: NYU Press

"From using clamshell razors and homemade lye depilatories in the colonial era to using diode lasers and prescription pharmaceuricals in the twenty-first century, Americans have gone to great lengths to remove body hair demmed unsightly, unattractive, or unhealthy. In Plucked, Rebecca M. Herzig examines both the causes and consequences of routine hair removal in the U.S. Plucked illuminates some of the broad social and environmental effects of seemingly 'personal' choices: widespread experimentation on animals, exploitation of workers, exacerbation of racial divisions, and more. An engrossing, multidimensional history of fulctural attitudes toward body hair and the increasingly sophisticated tools used to remove it, Plucked reveals the complex political significance of even the most mundane activities of modern life."--Back cover.

Principles of Knowledge Representation and Reasoning
  • Language: en
  • Pages: 696
Logics in Artificial Intelligence
  • Language: en
  • Pages: 528

Logics in Artificial Intelligence

This book constitutes the refereed proceedings of the 10th European Conference on Logics in Artificial Intelligence, JELIA 2006. The 34 revised full papers and 12 revised tool description papers presented together with 3 invited talks were carefully reviewed and selected from 96 submissions. The papers cover a range of topics within the remit of the Conference, such as logic programming, description logics, non-monotonic reasoning, agent theories, automated reasoning, and machine learning.

Fuzzy Sets, Logics and Reasoning about Knowledge
  • Language: en
  • Pages: 421

Fuzzy Sets, Logics and Reasoning about Knowledge

Fuzzy Sets, Logics and Reasoning about Knowledge reports recent results concerning the genuinely logical aspects of fuzzy sets in relation to algebraic considerations, knowledge representation and commonsense reasoning. It takes a state-of-the-art look at multiple-valued and fuzzy set-based logics, in an artificial intelligence perspective. The papers, all of which are written by leading contributors in their respective fields, are grouped into four sections. The first section presents a panorama of many-valued logics in connection with fuzzy sets. The second explores algebraic foundations, with an emphasis on MV algebras. The third is devoted to approximate reasoning methods and similarity-based reasoning. The fourth explores connections between fuzzy knowledge representation, especially possibilistic logic and prioritized knowledge bases. Readership: Scholars and graduate students in logic, algebra, knowledge representation, and formal aspects of artificial intelligence.

Proof Theory of Modal Logic
  • Language: en
  • Pages: 317

Proof Theory of Modal Logic

Proof Theory of Modal Logic is devoted to a thorough study of proof systems for modal logics, that is, logics of necessity, possibility, knowledge, belief, time, computations etc. It contains many new technical results and presentations of novel proof procedures. The volume is of immense importance for the interdisciplinary fields of logic, knowledge representation, and automated deduction.

The Case Against Johann Reuchlin
  • Language: en
  • Pages: 196

The Case Against Johann Reuchlin

A re-examination of the case of Johann Reuchlin, one of the best-known controversies of the 16th century.

Belief Change
  • Language: en
  • Pages: 452

Belief Change

Belief change is an emerging field of artificial intelligence and information science dedicated to the dynamics of information and the present book provides a state-of-the-art picture of its formal foundations. It deals with the addition, deletion and combination of pieces of information and, more generally, with the revision, updating and fusion of knowledge bases. The book offers an extensive coverage of, and seeks to reconcile, two traditions in the kinematics of belief that often ignore each other - the symbolic and the numerical (often probabilistic) approaches. Moreover, the work encompasses both revision and fusion problems, even though these two are also commonly investigated by diff...

Symbolic and Quantitative Approaches to Reasoning and Uncertainty
  • Language: en
  • Pages: 408

Symbolic and Quantitative Approaches to Reasoning and Uncertainty

In recent years it has become apparent that an important part of the theory of artificial intelligence is concerned with reasoning on the basis of uncertain, incomplete, or inconsistent information. A variety of formalisms have been developed, including nonmonotonic logic, fuzzy sets, possibility theory, belief functions, and dynamic models of reasoning such as belief revision and Bayesian networks. Several European research projects have been formed in the area and the first European conference was held in 1991. This volume contains the papers accepted for presentation at ECSQARU-93, the European Conference on Symbolicand Quantitative Approaches to Reasoning and Uncertainty, held at the University of Granada, Spain, November 8-10, 1993.