This book constitutes the refereed proceedings of the 7th International Workshop on Algorithmic Learning Theory, ALT '96, held in Sydney, Australia, in October 1996.
The 16 revised full papers presented were selected from 41 submissions; also included are eight short papers as well as four full length invited contributions by Ross Quinlan, Takeshi Shinohara, Leslie Valiant, and Paul Vitanyi, and an introduction by the volume editors. The book covers all areas related to algorithmic learning theory, ranging from theoretical foundations of machine learning to applications in several areas.

Tissue engineering is a multi-disciplinary field that is continually evolving and functions through the amalgamation of principles and practices derived from materials science, clinical medicine and the basic biological sciences. The goals of tissue engineering based therapies are to reconstitute the anatomic milieu and physiological function of diseased or damaged tissue in order to improve the poorly functioning target organ. With the advent of new synthetic polymers and advancements in stem cell biology, the combinatorial and/or synergistic effects of these disciplines has greatly advanced tissue engineering as a whole, particularly in the field of bladder tissue engineering. This book focuses on the current state of bladder tissue engineering with a specific emphasis on the use of autologous and allogenic cell sources, as well as biologic and synthetic matrices that influence cell growth and differentiation that can be used for future bladder tissue engineering applications.