In our day-to day-lives we constantly make decisions that are simply "good enough" rather than optimal. This may be to save time and trouble, or, for example, to avoid conflict with colleagues. Most computer-based decision-making algorithms, on the other hand, doggedly seek the optimal solution based on rigid criteria and reject any others. In this book, Professor Wynn Stirling outlines an alternative approach, using novel algorithms and techniques to model more closely the way humans make decisions. Building on traditional decision and game theory, these techniques allow decision-making systems to cope with more subtle situations where self and group interest conflict, perfect solutions can't be found, and human issues need to be taken into account - in short, more closely modeling the way humans make decisions. The book will therefore be of great interest to engineers, computer scientists, and mathematicians working on artificial intelligence and expert systems.