CABOT: An Adaptive Approach to Case-Based Search
نویسندگان
چکیده
T h i s paper describes C A B O T , a case-based syst e m t h a t is able to ad jus t i ts re t r ieva l and adapt a t i o n met r ics , in a d d i t i o n to s to r ing cases. I t has been app l ied to the game of OTHELLO. Exper iments show t h a t C A B O T saves a b o u t ha l f as many cases as s imi la r systems t h a t do no t ad jus t the i r re t r ieva l and a d a p t a t i o n mechanisms. I t also consis tent ly beats these systems. These results suggest t h a t ex is t ing case-based systems could save fewer cases w i t h o u t reduci ng the i r cur rent levels o f per fo rmance . T h e y also demons t ra te t h a t i t is benef ic ial to d i s t i n guish fa i lures due to miss ing i n f o r m a t i o n , f au l t y re t r ieva l , and f au l t y a d a p t a t i o n .
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