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Hard bop is introduced here through the prism of Lee Morgan: Morgan helped develop the style as an alternative to bop's successor, cool jazz, as developed, in part, by Gerry Mulligan and Miles Davis, and hard bop began to fade with his murder. But the book tackles more than Morgan, and, in fact, more than hard bop: It's a fascinating account of the various musical streams colliding--sometimes melding-- in the 10 years between 1955 and 1965.
Rosenthal traces the evolution of hard bebop as bop declined ("bebop . . . had turned into something of a straitjacket . . . Many of its best practitioners were dead, and others . . . were in decline"). Musicians looked to R & B to revive bop, and a new "more emotionally expressive and more formally flexible style began to emerge." Rosenthal looks at the expressions of hard bop in such diverse artists as Sonny Rollins, the soulful Horace Silver ("The Preacher"), Cannonball Adderley, organist Jimmy Smith ("Midnight Special"), Jackie MacClean, and, to a lesser degree, Art Farmer, Andrew Hill, Mingus, and some of the pre-1965 John Coltrane (e.g., with Miles on "Cookin'"). Rosenthal perceptively notes that hard bebop was a "complicated set . . . of interlocking tendencies," rather than a static, easily defined style.
I enjoy this book because it explores a somewhat brief phenomenon, and shows how it developed, flourished, and then gave way to new elements. The writing is crisp, intelligent, energetic, and full of illustrative anecdotes that illuminate and entertain (not the dry pedantic treatise one might expect on this rather narrow topic). Rosenthal shows the connections between various elements of jazz, and presents it as a living, evolving, powerful force. Eleven chapters following the introduction, no pictures. Very highly recommended to jazz fans of any stripe.
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A 2-D book format is obviously not the optimal format for experiencing Rath's kinetic sculptures. Nevertheless, if you don't have the opportunity to go to one of his exhibits, the photographs of Rath's exhibited works at SITE Santa Fe is the next best thing.
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The emphasis in the book is on intelligent agents, which the authors characterize in chapter one. Agents are viewed as black boxes that take in knowledge, past experiences, goals/values, and observations and output actions. They define what they call a representation and reasoning system consisting of a language to communicate to a computer, a methodology for giving meaning to this language, and a collection of procedures for computation. They also outline the three applications domains they will be developing in the book: an autonomous delivery robot, a diagnostic assistant, and an infobot.
The authors expand upon the representation and reasoning system in chapter 2 in terms that are familiar from mathematical logic and computer science. A formal language, a semantics, and a proof procedure are the three essentials of an RRS. All of these elements are discussed in great detail, and concrete examples are given for all the main concepts. Readers without any background in logic may find the reading difficult, but with some effort it could be read profitably. The authors do a good job of presenting material that is usually delegated to texts on formal computer science.
In chapter three, the authors show how representational knowledge can be used for domain representation, querying, and problem solving. This is done via an example of electrical house wiring and the PROLOG-astute reader will find the presentation very straightforward. But LISP programmers will also see its influence and the discussion on lists. An application is given in computational linguistics, namely that of definite clauses for context-free grammars.
A discussion of searching is given in chapter 4, in the context of potential partial solutions to a problem, with the hope that these will truly be real solutions for the problem at hand. Graph searching, blind search strategies, heuristic searching, and refinements of these are all discussed with great clarity. And, because of their importance in applications, dynamic programming and constraint classification problems are overviewed, albeit very briefly.
Chapter 5 turns to the topic of how to choose a representation langauge for knowledge. The authors detail the criteria for comparing different languages or logics in terms of expressiveness, worse-case complexity, and naturalness. Most important in this chapter is the discussion on qualitative versus quantitative representations.
This is followed in chapter 6 by a discussion of the user interactions to a knowledge-based system in terms of a meta-interpreter that produces knowledge acquistion, debugging, etc.
The next chapter shows how definite clause representation and reasoning systems can be extended to include the relation of equality and negation, and quantification of variables. This sets up naturally a discussion of first-order predicate calculus, but only a brief overview is given. A very short treatment of modal logic is given.
Chapter 8 considers agents that act and reason in time, with three representations given for reasoning about time. These are the STRIPS representation (developed at Stanford University), the situation calculus, and the event calculus. It is then shown how these can be used to reason and produce plans to achieve goals. Although brief, the discussion is very interesting, and the authors give good references for further reading.
The authors generalize their discussions to assumption-based reasoning in chapter 9, which up until this chapter has been restricted to reasoning from knowledge bases. Nonmonotonic reasoning is defined, along with abduction, which is a form of reasoning different from both deduction and induction, and which emphasizes hypothesis formation.
Chapter 10 considers the more realistic situation whre the agents have incomplete or uncertain knowledge. This naturally brings up a discussion of probability, which the authors define as the study of how knowledge affects belief. They distinguish between evidence and background knowledge, the latter which is stated in terms of conditional probabilities, the former characterized by what is true in the situation being studied. Belief networks are introduced as a graphical representation of conditional independence, these graphs being directed and also acyclic (the latter for reasons of causality). An algorithm for determining the posterior distribution of belief networks is given, and is based on the idea that a belief network specifies a factorization of the joint probability distribution. A brief overview of decision networks is also given.
The important topic of learning theory is overviewed in chapter 11. And, naturally, neural networks make their appearance here, although the discussion is very brief. PAC learning is also treated, as well as Bayesian learning. Unfortunately, the important field of inductive logic programming is not discussed, but some references are given.
The last chapter covers artificial purposive agents, otherwise known as robots. This is a vast subject, and only a general overview is given here, but the authors do a good job of showing how robots can be characterized within the concepts outlined in the book. Dynamical systems are used to represent the agent function for a robot. Readers familiar with the theory of dynamical systems will see the state transition function appear here in a more general context. The states of an agent at time t encode all of the information about its history. The state transition functions acts on the states and percepts, with the percepts playing the role of time in the usual dynamical system.
The appendices include a terminology list and a short introduction to PROLOG, along with a few examples of PROLOG code applied to some of the concepts in the book. Although very general, the inclusion of these examples are of further help in understanding the material in the book.
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On top of this, Drummond gives only idiomatic translations, not literal ones. Most obscenity dictionaries do this to some extent, but many of Drummond's translations are simply wrong. (I'd cite examples, but they'd keep this review from being published.) Literal translations are funnier, and give a much better sense of what exactly a culture finds obscene.
If you're reading pre-20th century Russian literature in Russian, buy this book. Otherwise, buy Christina Kunitskaya-Peterson's "International Dictionary of Obscenities." It is much more user-friendly and has four other languages to boot.