Expert Systems and the Environment History of Expert Systems

Expert systems are computer programs that can perform some task which typically requires the capabilities of a skilled human. These tasks are usually of a decision-making nature rather than physical actions. Examples of such tasks are managing water levels in a wetland, forecasting weather conditions, assessing environmental impacts, and selecting mitigation measures for environmental hazards. As computer programs that contain human expertise, they are referred to variously by the labels expert systems, knowledge-based systems, inference systems or rule-based systems. Expert systems have evolved as a highly commercializable offshoot of research in the subfield of computer science called artificial intelligence (AI). Since its unofficial inception at the AI has had as one of its primary goals the creation of 'thinking machines.' While this ambitious goal has not yet been attained to anyone's acknowledgment, there have been substantial advances in what we now know about human thinking and learning. Along the way, research in AI from the late 1950s to the 1970s at Stanford, MIT and Carnegie-Mellon Universities provided some very powerful techniques for codifying human experience and knowledge so that computers can store it and apply it to solve practical problems. The mid-1970s saw the emergence of the first expert systems for applications such as medical diagnosis (Mycin, by Shortliffe), chemical data analysis (Dendral, by Lindsay and others), and mineral exploration (Prospector, by Duda and others). For further information , see Barr and Feigenbaum (1982). Since that time, the