In our day-to-day lives we constantly make decisions which are simply 'good enough' rather than optimal. Most computer-based decision-making algorithms, on the other hand, doggedly seek only the optimal solution based on rigid criteria and reject any others. In this book, Professor Stirling outlines an alternative approach, using novel algorithms and techniques which can be used to find satisficing solutions. Building on traditional decision and game theory, these techniques allow decision-making systems to cope with more subtle situations where self and group interests conflict, perfect solutions can't be found and human issues need to be taken into account - in short, more closely modelling 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. 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. In our day to day lives we constantly make decisions which are simply 'good enough' rather than optimal - a type of decision for which Professor Wynn Stirling has adopted the word 'satisficing'. Most computer-based decision making algorithms, on the other hand, doggedly seek only the optimal solution based on rigid criteria and reject any others. In this book, Professor Stirling outlines an alternative approach, using novel algorithms and techniques which can be used to find satisficing solutions. Building on traditional decision and game theory, these techniques allow decision making systems to cope with more subtle situations where self and group interests conflict, perfect solutions can't be found and human issues need to be taken into account - in short, more closely modelling the way humans make decsions. The book will therefore be of great interest to engineers, computer scientistsand mathematicians working on artificial intelligence and expert systems We constantly make decisions which are simply "good enough" rather than optimal--a type of decision for which Wynn Stirling has adopted the word "satisficing". Most computer decision making algorithms, however, seek only the optimal solution based on rigid criteria and reject others. Outlining an alternative approach, this book uses novel algorithms and techniques to more closely model the way humans make decisions. It is, therefore, of interest to engineers, computer scientists and mathematicians working on artificial intelligence and expert systems This book outlines an alternative approach to mathematical decision-making, using novel algorithms and techniques to more closely model the way humans make decisions. It will be of great interest to engineers, computer scientists and mathematicians working on artificial intelligence and expert systems. This book outlines an alternative approach to mathematical decision making, using novel algorithms and techniques to more closely model the way humans make decisions. It will be of great interest to engineers, computer scientists and mathematicians working on artificial intelligence and expert systems
An alternative approach to mathematical decision making for AI and expert systems engineers and scientists.
The disciplines of science and engineering are complementary.
