Experience-based deductive learning

A method of deductive learning is proposed to con trol deductive inference Our goal is to improve prob lem solving time by experience when that experience monotonically adds knowledge to the knowledge base Accumulating and exploiting experience are done by the schemes of knowledge migration and knowledge shadowing Knowledge migration generates speci c migrated rules from general migrating rules and accumulates deduction experience represented by speci city relationships between migrating and migrated rules Knowledge shadowing recognizes rule redun dancies during a deduction and prunes deduction branches activated from redundant rules Three prin ciples for knowledge shadowing are suggested depend ing on the details of deduction experience representa tion