I, realy like this book. I liked it because it ties sports, friendship, teamwork, and real life altogether. Although this book is not completely believable it addresses a lot of youth situations. This book is good for kids, whether they play base ball or not.

I picked this book up in San Francisco a few years ago. The book is set in Southern Ontario. Which happens to be my hometown stomping ground. Perhaps this grants me a bias, however I do feel that this book was well written. The characters seem very suitable for each other. I don't want to ruin the premise for anyone but suffice it to say - good lesbian versus evil. The evil source was surprising considering the location, yet not far fetched. I still own this book. I am writing this review because I was looking to find a new book by Deb Ellis. I hope she still wishes to continue her writing. Thank you.

Creativity is perhaps one of the most profound, important and still mysterious domains of study open to us.

From 1908, when Poincare wrote his landmark essay on creativity and psychology of thought in mathematical invention, through 1950 when Guilford brought this neglected topic back into the mainstream of psychological study, through to today where we have a plethora of views regarding creativity and the creative process, it remains a fascinating study.

This book is an excellent introduction to and reference work to creativity and the creative process as viewed by professionals in the field of psychology. As such, it is immensely useful to anyone wanting to or needing to orient themselves in this field, but it also suffers from the limitations inherent in the methodology and focus of the field itself. These problems revolve around the need to make psychology a respectable 'science' and raise methodological difficulties with evidence from testimonies of creative people and from our own personal experience - two of the most important sources of knowledge for creativity - and with the need to reformulate insights as testable hypotheses. These problems while generally present in psychology as a discipline are exascerbated in the study of creativity, due primarily to the elusive and potentially mysterious phase of the psychological creative process when 'illumination' or insight occurs, and the difficulty or perhaps impossibility of studying it any way other than internal observation or through reports of others' observations of their creative experience.

The book is fair and even handed in its approach, raising many of these difficulties in the discussion and reporting fairly on a wide range of different views in the historical and modern context as well as giving an excellent outline of the field.

This book is an excellent book with which to orient oneself in a professional psychological understanding of creativity. However, if you are mainly interested in practically developing and applying creativity and the creative process, popular authors such as Robert Fritz ('Path of Least Resistance') or the wide range of authors who report on the personal experience and views of outstanding creators (eg 'The Creative Process' by Brewster Ghiselin) may be more inspirational, applicable, useful and satisfying.

P.B. Ellis does a reasonably good job of summarizing the scholarship on the Cromwellian era in Irish History. His presentation of events provides enough details for the reader to appreciate the complexities of Anglo-Irish politics during this time. And yet, the reader doesn't have to already be an expert in the field to understand the big picture.

This book is a self help book that helps the reader by going through various scenarios and cognitive therapy. It gives you the right way of doing things and the wrong way (it's very black and white). Check it out sometime.

This book is a good overview of what is needed to effectively train staff. It covers everything from adult learning to evaluating programs. It doesn't offer depth on any topic, but if someone needs to learn about training quickly and easily than this is an excellent source.

Human Being is a very well constructed book full of the helpful kind of advice your grandmother would give you if you hadn't sent her off to the nursing home. Seriously, I love this book. It is organized into four main sections as implied by the subtitle. Then each of those sections is subdivided into numerous small articles. Each article gives insight into specific human problems, asks relevant questions of the reader, and offers helpful advice and activities to help the reader work through the problem. This book is as interactive and multimedia as a printed book can be. It is also my best friend when I have no one to talk to.

Interest in inductive logic programming has waxed and waned over the last decade, but never fallen to zero. This book is a summary of what was known in the field in 1994, and much has changed since then. It can however still serve as an introduction to the field of inductive logic programming, in spite of its publication date. Most of the current research and applications of inductive logic programming has concentrated on introducing stochasticity into logic programming and on how to incorporate reasoning with numerics into the framework.

The authors emphasize the empirical aspects of inductive logic programming and its applications, but do spend the first few chapters detailing the theoretical foundations of the subject. The characterize machine learning paradigms as inductive, deductive, learning with genetic algorithms, and learning with neural nets. They rule out neural net learning as being a true learning system since it does not pass the "Michie strong criterion", i.e. learning must acquire new knowledge which must be understandable by humans. They do not elaborate on why neural nets fail to meet this criterion. Inductive learning of course is what they consider exclusively in the book, with inductive concept learning essentially consisting of the learning of how to recognize objects in the concept, the concept being a subset of objects in universal set of objects or observations. To define inductive concept learning more rigorously the authors employ the concept of a covering of an object, which means essentially that the description of the object satisfies the description of the concept. The object description is thus "covered" by the concept description. Notions of completeness and consistency of hypotheses are then introduced, with completeness being the requirement that the hypothesis cover all positive examples and no negative ones, while consistency meaning that it does not cover any of the negative examples. These ideas are then generalized to the case where background knowledge is present. Inductive logic programming systems are then defined as those that induce hypotheses in the form of logic programs. These systems are partitioned into those that learn predicates from scratch, called empirical ILP systems, and those that learn multiple predicates, called interactive ILP systems. The authors then discuss briefly the systems that were available at the time of writing. Only empirical ILP systems are considered by the authors in the book, with emphasis on the systems LINUS and FOIL, which were the dominant ones at the time of writing.

Because of its popularity and effectiveness in logic programming, the authors employ Prolog to introduce the basic theory of logic programming. Other languages have been developed since then with ILP applications in mind, one of these being Progol. Symbolic programming languages, such as Mathematica and Maple, can also be used, and very effectively. The essentials of logic programming discussed in the book have no doubt been seen by the reader, and some familiar concepts such as Horn clauses and resolution are discussed by the authors. The goal of empirical ILP then is to find a complete and consistent definition for an unknown predicate given a set of examples and background knowledge. Concept learning is viewed as a search problem, with states in the search space being concept descriptions. The goal is to find states that satisfy a quality criterion, and a learning algorithm is characterized in terms of the structure of its search space, its search strategy, and the search heuristics. The structure of the search space is characterized by a "theta-subsumption lattice", which gives the structure of the search space of program clauses, and which can be searched blindly or heuristically. Theta-subsumption provides the basis for a "bottom-up" ILP technique, namely that of the building of least general generalizations from training examples relative to background knowledge, and a "top-down" technique of the searching of refinement graphs. These techniques and the technique of inverse resolution are discussed in detail by the authors. The idea of inverse resolution will seem natural to the reader familiar with the related (but inverted) procedure in deductive (propositional) logic. Inverse resolution inverts the SLD-resolution proof procedure for definite programs.

Most of the book is devoted to an overview of the FOIL system and how it can be implemented to do practical inductive logic programming. The search routines used by FOIL are hill-climbing strategies, and the authors discuss ways that have been used to improve on these. Since this book was written, an ILP system called SFOIL has appeared that takes advantage of the view of induction of hypotheses as an optimization problem. Interestingly, SFOIL uses a generalization of simulated annealing to do this, based on Markovian neural networks. The authors also review the GOLEM ILP programming language, which is based on the notion of relative least general generalization, again a bottom-up search of the theta-subsumption lattice. Other ILP languages, such as MOBAL and MPL are also reviewed. In addition, the LINUS IPL system is reviewed, which exploits background knowledge in learning both propositional and relational descriptions. Deduction plays a major role in the LINUS system, as well as the transformation of relational descriptions to a propositional learning task. Both the FOIL and the LINUS systems are characterized with respect to refinement operators and refinement graphs, which allows a comparison of the expressiveness of their hypothesis languages and the search costs associated with these systems.

The authors also discuss how to handle imperfect data in ILP, and show the role of heuristics in doing this. Random errors in training examples and background knowledge, sparse training examples, inexact description of target concepts, and missing values in training examples all need to be dealt with when using ILP, and various techniques are oultined by the authors to do this. Several interesting applications of ILP are given in the book, including medical diagnostics, finite element methods, qualitative modeling of dynamical systems, and predicting protein secondary structure. The role of ILP in bioinformatics has taken on more importance in recent years, and this trend will no doubt continue.

Dr. Ellis and Dr. Stuen have collected the background theory and the most current research related to a well-known strategy for maximizing student interest and achievement. Interdisciplinary curriculum combines compatible knowledge and skills that traditionally would be addressed in separate disciplines or simply overlooked. They present all the pieces necessary for deciding on such an approach, using a very readable but authoritative style. I like the format for reviewing each one. The examples are a thoughtful range that represent the strategy, and they include contact information for active practitioners as well as current publications. For anyone caught up in the testing frenzy that has reduced many classes to ancient drill-and-kill methods, this book is an inspiration. I think it is accessible to any educated person, not just grad students in education beefing up their knowledge base, but also to school board members who may have been approached to fund a program in this category. Great combination how-to and how-come.

More than just a dry run for his liturgical Christian music drama PARSIFAL, the German composer's personal look at the life of Christ merges the traditional Passion story with his own brand of revolutionary politics, proving true novelist Reynolds Price's words that "virtually all post-Gospel lives of Jesus [have] told us far more about their authors than their subject." Yet for a man so often identified with anti-Semitism, readers will be surprised that Wagner's mystery play is remarkably free of racial bias or slurs. Not only are the Jews not scapegoated as the Christ-killers of Medieval lore, but the portrayal of Judas as a heroic freedom fighter echoes the portrait in Nikos Kazantzakis' THE LAST TEMPTATION OF CHRIST. (One wonders if this interpretation tricked down to Kazantzakis during his intensive studies of Wagner friend-turned-foe Friedrich Nietzsche.)

All in all, fascinating material not only for musicologists, historians, and Wagnerites, but for those interested in the Christology as seen though the eyes of historical personages.