Evans & Levinson's (E&L's) major point is that human languages are intriguingly diverse rather than (like animal communication systems) uniform within the species. This does not establish a about language universals, or advance the ill-framed pseudo-debate over universal grammar. The target article does, however, repeat a troublesome myth about Fitch and Hauser's (2004) work on pattern learning in cotton-top tamarins.

What can computers do in principle? What are their inherent theoretical limitations? These are questions to which computer scientists must address themselves. The theoretical framework which enables such questions to be answered has been developed over the last fifty years from the idea of a computable function: intuitively a function whose values can be calculated in an effective or automatic way. This book is an introduction to computability theory (or recursion theory as it is traditionally known to mathematicians). Dr Cutland (...) begins with a mathematical characterisation of computable functions using a simple idealised computer (a register machine); after some comparison with other characterisations, he develops the mathematical theory, including a full discussion of non-computability and undecidability, and the theory of recursive and recursively enumerable sets. The later chapters provide an introduction to more advanced topics such as Gildel's incompleteness theorem, degrees of unsolvability, the Recursion theorems and the theory of complexity of computation. Computability is thus a branch of mathematics which is of relevance also to computer scientists and philosophers. Mathematics students with no prior knowledge of the subject and computer science students who wish to supplement their practical expertise with some theoretical background will find this book of use and interest. (shrink)

This unique book presents a comprehensive and rigorous treatment of the theory of computability which is introductory yet self-contained. It takes a novel approach by looking at the subject using computation models rather than a limitation orientation, and is the first book of its kind to include software. Accompanying software simulations of almost all computational models are available for use in conjunction with the text, and numerous examples are provided on disk in a user-friendly format. Its applications to computer science (...) itself include interesting links to programming language theory, compiler design theory, and algorithm design. The software, numerous examples, and solutions make this book ideal for self-study by computer scientists and mathematicians alike. (shrink)

Research on implicit learning - a cognitive phenomenon in which people acquire knowledge without conscious intent or awareness - has been growing exponentially. This volume draws together this research, offering the first complete reference on implicit learning by those who have been instrumental in shaping the field. The contributors explore controversies in the field, and examine: functional characteristics, brain mechanisms and neurological foundations of implicit learning; connectionist models; and applications of implicit learning to acquiring new mental skills.