Learning Novel Domains Through Curiosity and Conjecture

This paper describes DIDO, a system we have developed to carry out exploratory learning of unfamiliar domains without assistance from an external teacher. The program incorporates novel approaches to experience generation and representation generation. The experience generator uses a heuristic based on Shannon's uncertainty function to find informative examples. The representation generator makes conjectures on the basis of small amounts of evidence and retracts them if they prove to be wrong or useless. A number of experiments arc described which demonstrate that the system can distribute its learning resources to steadily acquire a good representation of the whole of a domain, and that the system can readily acquire both disjunctive and conjunctive concepts even in the presence of noise.

• Type: Conference
• Year: 1989
• Where: IJCAI
• Authors: Paul D. Scott, Shaul Markovitch
• Keywords: Generator Makes Conjectures, IJCAI 1989, IJCAI 2007, Representation Generation, Shannon's Uncertainty Function