PROSPECTOR编辑历史

# PROSPECTOR

PROSPECTOR is an early rule-based expert system developed in the 1970s at SRI International for mineral exploration, specifically to assist geologists in evaluating potential ore deposits. It represents a landmark application of artificial intelligence in the field of geology, combining knowledge from human experts with a probabilistic reasoning framework. The system uses a hierarchical model of geological evidence to infer the likelihood of various mineral deposit types, such as porphyry copper or uranium deposits, and has been credited with the discovery of a significant molybdenum deposit.

## 1 Development and Historical Context

### 1.1 Origins at SRI International (1970s)

The development of PROSPECTOR began in the early 1970s at SRI International (formerly Stanford Research Institute) in Menlo Park, California. Funded primarily by the U.S. Geological Survey and the National Science Foundation, the project aimed to create an automated tool that could assist field geologists in assessing mineral prospectivity. The impetus came from the growing recognition that expert knowledge about ore deposits was scarce and that a computerized system could capture and distribute that expertise consistently.

### 1.2 Influences from DENDRAL and MYCIN

PROSPECTOR was heavily influenced by two pioneering expert systems of the era: DENDRAL (for organic chemistry structure elucidation) and MYCIN (for medical diagnosis). From DENDRAL it borrowed the concept of encoding domain-specific heuristic rules; from MYCIN it adopted the idea of rule-based inference with uncertainty management. However, while MYCIN used certainty factors derived from ad hoc psychology, PROSPECTOR opted for a more formal Bayesian probabilistic framework, a key distinction.

### 1.3 Key Contributors: Richard O. Duda, John Gaschnig, Peter E. Hart

The core development team included Richard O. Duda, who led the project and contributed to the probabilistic inference design; John Gaschnig, who implem