Name
Abstract | ||
|---|---|---|
Intelligent system, can explore only tiny subsets of their potential external and conceptual worlds. To increase their effective capacities, they must develop efficient forms of representation, access, and operation. In this paper we develop several techniques which do not sacrifice expressibility, yet enable programs to (semi-)automatically improve themselves and thus increase their productivity. The basic source of power is the ability to predict the way that the program will be used in the future, and to tailor the program to expedite such UBEB. Caching, abstraction, and expectation-simplified processing are principal examples of such techniques. We discuss the use of these and other economic principles for modern AI systems. Our analysis leads to some counterintuitive ideas (e.g., favoring redundancy over minimal storage in inheritance hierarchies). |
Year | Venue | Keywords |
|---|---|---|
1979 | IJCAI | expectation-simplified processing,counterintuitive idea,conceptual world,minimal storage,artificial intelligence system,inheritance hierarchy,economic principle,cognitive economy,basic source,intelligent system,efficient form,effective capacity,artificial intelligent |
Field | DocType | ISBN |
Counterintuitive,Abstraction,Computer science,Redundancy (engineering),Artificial intelligence,Hierarchy,Cognition,Machine learning | Conference | 0-934613-47-8 |
Citations | PageRank | References |
7 | 5.39 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Douglas B. Lenat | 1 | 1986 | 895.91 |
| Frederick Hayes-Roth | 2 | 1345 | 1193.66 |
| Philip Klahr | 3 | 114 | 158.78 |