Case-by-case problem solving

Abstract

Case-by-case Problem Solving solves each occurrence, or case, of a problem using available knowledge and resources on the case. It is different from the traditional Algorithmic Problem Solving, which applies the same algorithm to all occurrences of all problem instances. Case-by-case Problem Solving is suitable for situations where the system has no applicable algorithm for a problem. This approach gives the system flexibility, originality, and scalability, at the cost of predictability. This paper introduces the basic notion of Case-by-case Problem Solving, as well as its most recent implementation in NARS, an AGI project. Copyright © 2008, The Second Conference on Artificial General Intelligence (AGI-09.org). All rights reserved.