TY - JOUR AU - Slade, Stephen PY - 1991/03/15 Y2 - 2024/03/28 TI - Case-Based Reasoning: A Research Paradigm JF - AI Magazine JA - AIMag VL - 12 IS - 1 SE - Articles DO - 10.1609/aimag.v12i1.883 UR - https://ojs.aaai.org/aimagazine/index.php/aimagazine/article/view/883 SP - 42 AB - Expertise comprises experience. In solving a new problem, we rely on past episodes. We need to remember what plans succeed and what plans fail. We need to know how to modify an old plan to fit a new situation. Case-based reasoning is a general paradigm for reasoning from experience. It assumes a memory model for representing, indexing, and organizing past cases and a process model for retrieving and modifying old cases and assimilating new ones. Case-based reasoning provides a scientific cognitive model. The research issues for case-based reasoning include the representation of episodic knowledge, memory organization, indexing, case modification, and learning. In addition, computer implementations of case-based reasoning address many of the technological shortcomings of standard rule-based expert systems. These engineering concerns include knowledge acquisition and robustness. In this article, I review the history of case-based reasoning, including research conducted at the Yale AI Project and elsewhere. ER -