e to solve the problem" states Satter. A few more implementations of artificial intelligence include knowledge-based systems, expert systems, and case-based reasoning. All of these are relatively similar because they all use a fixed set of rules. Knowledge-based systems (KBS) are systems that depend on a large base of knowledge to perform difficult tasks (Patterson 13). KBS get their information from expert knowledge that has been programmed into facts, rules, heuristics and procedures. However, the power of a knowledge-based system is only as good as the knowledge given to it. Therefore, the knowledge section is usually separate from the control system and can be updated independently. This enables system updates and additional information to be added in a more efficient manner then making a whole new system from scratch (O'Shea 162). Expert systems have proven effective in a number of problem domains that usually require human intelligence (Patterson 326). They were developed in the research labs of universities in the 1960's and 1970's. Expert systems are primarily used as specialized problem solvers. The areas that this can cover are almost endless. This can include law, chemistry, biology, engineering, manufacturing, aerospace, military operations, finance, banking, meteorology, geology, and more. Expert systems use knowledge instead of data to control the solution process. "In knowledge lies the power" is a theme repeated when building such systems. These systems are capable of explaining the answer to the problem and why any requested knowledge was necessary. Expert systems use symbolic representations for knowledge and perform computations through manipulations of the different symbols (Patterson 329). But perhaps the greatest advantage to expert systems is their ability to realize their l! imits and capabilities. Case-based reasoning (CBR) is similar to expert system because theoretically they could use they sam...
