Case-Based Reasoning in Parallel Environments

Case-Based Reasoning may help address problems with difficult mathematical formalizations in artificial intelligence, such as decision making. While these models usually carry a series of structural and functional dependencies that may affect parallel speedup and efficiency, there are other performance features that justify parallel implementations. This paper presents a reworking of the classical structures and methods of Case-Based Reasoning, redefined for parallel environments, alongside performance analysis techniques suitable for symbolic representations.