This volume, which includes some previously published work and the most recent writings of the late Martin Braine and his colleagues, will be of interest to cognitive scientists, philosophers of mind and logicians, developmentalists, and psycholinguists.

Over the past decade, the question of whether there is a mental logic has become subject to considerable debate. There have been attacks by critics who believe that all reasoning uses mental models and return attacks on mental-models theory. This controversy has invaded various journals and has created issues between mental logic and the biases-and-heuristics approach to reasoning, and the content-dependent theorists. However, despite its pertinence to current issues in cognition, few cognitive scientists really know what the mental-logic theory is, and misapprehensions are prevalent. This volume is a comprehensive presentation of the theory of mental logic and its implications for cognition and development, including the acquisition of language. The theory offered here has three parts. Part I is the mental logic per se that contains a set of inference schemas. Part II is a reasoning program that applies the schemas in lines of reasoning, including a direct-reasoning routine and more sophisticated indirect-reasoning strategies. Part III of the theory is pragmatic, proposing that the basic meaning of each logic particle is in the inferences that are sanctioned by its inference schemas.

Lance Rips describes a unified theory of natural deductive reasoning and fashions a working model of deduction, with strong experimental support, that is capable of playing a central role in mental life. In this provocative book, Lance Rips describes a unified theory of natural deductive reasoning and fashions a working model of deduction, with strong experimental support, that is capable of playing a central role in mental life. Rips argues that certain inference principles are so central to our notion of intelligence and rationality that they deserve serious psychological investigation to determine their role in individuals' beliefs and conjectures. Asserting that cognitive scientists should consider deductive reasoning as a basis for thinking, Rips develops a theory of natural reasoning abilities and shows how it predicts mental successes and failures in a range of cognitive tasks. In parts I and II of the book, Rips builds insights from cognitive psychology, logic, and artificial intelligence into a unified theoretical structure. He defends the idea that deduction depends on the ability to construct mental proofs—actual memory units that link given information to conclusions it warrants. From this base Rips develops a computational model of deduction based on two cognitive skills: the ability to make suppositions or assumptions and the ability to posit sub-goals for conclusions. A wide variety of original experiments support this model, including studies of human subjects evaluating logical arguments as well as following and remembering proofs. Unlike previous theories of mental proof, this one handles names and variables in a general way. This capability enables deduction to play a crucial role in other thought processes, such as classifying and problem solving. In part III, Rips compares the theory to earlier approaches in psychology which confined the study of deduction to a small group of tasks, and examines whether the theory is too rational or too irrational in its mode of thought.

Tend the zen garden of your mind with three different types of Japanese logic puzzles. This book features three different types of elegant, handcrafted Japanese logic puzzles from Nikoli: masyu, yajilin, and suraromu (also called "slalom")--90 puzzles in all. The choice of puzzle types was inspired by the image of raking a zen garden, as each involves drawing a long, winding path. Like sudoku, the puzzles have simple-to-understand rules, and solvers will be able to ease into the book with plenty of easy- and medium-difficulty puzzles.

A cutting-edge reference source for the interdisciplinary field of computational cognitive modeling.