Eyke Hüllermeier, “Case-Based Approximate Reasoning”
Springer; 1 edition (March 5, 2007) | ISBN: 140205694X | 372 pages | PDF | 4,4 Mb

Case-based reasoning (CBR) has received a great deal of attention in recent years and has established itself as a core methodology in the field of artificial intelligence. The key idea of CBR is to tackle new problems by referring to similar problems that have already been solved in the past. More precisely, CBR proceeds from individual experiences in the form of cases. The generalization beyond these experiences typically relies on a kind of regularity assumption demanding that ’similar problems have similar solutions’.

Wynn C. Stirling, “Satisficing Games and Decision Making: With Applications to Engineering and Computer Science”
Cambridge University Press | ISBN 052103891X | 2007 | PDF | 267 Pages | 1.4 Mb

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.