PROSPECTOR[right]
One of the largest area of applications of artificial intelligence is in expert systems, or knowledge based systems as they are often known.
This type of system seeks to exploit the specialized skills or information held by of a group of people on specific areas. It can be thought of as a computerized consulting service. It can also be called an information guidance system. Such systems are used for prospecting medical diagnosis or as educational aids. They are also used in engineering and manufacture in the control of robots where they inter-relate with vision systems. The initial attempts to apply artificial intelligence to generalized problems made limited progress as we have seen but it was soon realized that more significant progress could be made if the field of interest was restricted.
PROSPECTOR
Consultation system to assist geologists working in mineral exploration.
developed by Hart and Duda of SRI International.
Problem domain: Evaluation of the mineral potential of a geological site or region.
multi_ disciplinary decision making PROSPECTOR deal with geologic sitting, structural controls ,and kind of rocks, minerals and alteration products present or suspected.
Target Users
Exploration geologist who is in the early part of investigating an exploration site.
Characteristics of a particular “prospect” (exploration site) volunteered by expert
(e.g.geologic setting, structural controls, and kinds of rocks minerals, and alteration products present or suspected)
PROSPECTOR compares observations with stored models of ore deposits
PROSPECTOR notes similarities, differences and missing information
(POSPECTOR asks for additional information if neccessary)
PROSPECTOR assesses the mineral potential of the prospect
system has been kept domain independent, it matches data from a site against models describing regional and local characteristics favorable for specific ore deposits, the input data are assumed to be incomplete and uncertain .
PROSPECTOR' Knowledge Base
The knowledge representation scheme used by the developer's of PROSPECTOR is called 'the inference network': a network of connections between evidence and hypotheses.
In addition to the PROSPECTOR rule-base, the system also has a large taxonomic network : “hierarchical” data base containing super and sub ordinate relationship between the object of domain.
PROSPECTOR combines several of sources inconclusive information to form a conclusion of which it may be almost certain.
Each rule is associated with a number between 0 and 1 (CF, the 'certainty factor') representing certainty of the inference contained in the rule[/
right].One of the largest area of applications of artificial intelligence is in expert systems, or knowledge based systems as they are often known.
This type of system seeks to exploit the specialized skills or information held by of a group of people on specific areas. It can be thought of as a computerized consulting service. It can also be called an information guidance system. Such systems are used for prospecting medical diagnosis or as educational aids. They are also used in engineering and manufacture in the control of robots where they inter-relate with vision systems. The initial attempts to apply artificial intelligence to generalized problems made limited progress as we have seen but it was soon realized that more significant progress could be made if the field of interest was restricted.
PROSPECTOR
Consultation system to assist geologists working in mineral exploration.
developed by Hart and Duda of SRI International.
Problem domain: Evaluation of the mineral potential of a geological site or region.
multi_ disciplinary decision making PROSPECTOR deal with geologic sitting, structural controls ,and kind of rocks, minerals and alteration products present or suspected.
Target Users
Exploration geologist who is in the early part of investigating an exploration site.
Characteristics of a particular “prospect” (exploration site) volunteered by expert
(e.g.geologic setting, structural controls, and kinds of rocks minerals, and alteration products present or suspected)
PROSPECTOR compares observations with stored models of ore deposits
PROSPECTOR notes similarities, differences and missing information
(POSPECTOR asks for additional information if neccessary)
PROSPECTOR assesses the mineral potential of the prospect
system has been kept domain independent, it matches data from a site against models describing regional and local characteristics favorable for specific ore deposits, the input data are assumed to be incomplete and uncertain .
PROSPECTOR' Knowledge Base
The knowledge representation scheme used by the developer's of PROSPECTOR is called 'the inference network': a network of connections between evidence and hypotheses.
In addition to the PROSPECTOR rule-base, the system also has a large taxonomic network : “hierarchical” data base containing super and sub ordinate relationship between the object of domain.
PROSPECTOR combines several of sources inconclusive information to form a conclusion of which it may be almost certain.
Each rule is associated with a number between 0 and 1 (CF, the 'certainty factor') representing certainty of the inference contained in the rule