Title :
Case-based systems
Author :
Juell, Paul ; Paulson, Patrick
Author_Institution :
North Dakota State Univ., Fargo, ND, USA
Abstract :
Because reinforcement-trained case-based reasoning systems derive a similarity function through interaction with their environment, they can adapt to user needs. RETCBR techniques let researchers apply case-based reasoning in domains where case similarity is difficult to define.
Keywords :
case-based reasoning; learning (artificial intelligence); RETCBR; reinforcement-trained case-based reasoning systems; similarity function; Databases; Environmental economics; Feedback; Humans; Immune system; Indexing; Learning; Libraries; Probes; Testing;
Journal_Title :
Intelligent Systems, IEEE
DOI :
10.1109/MIS.2003.1217629
