New Development in Computer Software

1. Knowledge-based expert system

Knowledge-based expert system is an intelligent program that uses knowledge and inference procedures to solve problems that would be difficult to solve without human expertise.

2. Human information processor

 One of the popular models of the human information processor breaks it down into three major subsystems which are the perceptual subsystem, a cognitive subsystem, and a motor subsystem. The perceptual subsystem accepts inputs from the external world through its sensors, the cognitive subsystem interprets the inputs and triggers the motor subsystem to react to the input.

 Stimuli from the external world are the inputs to the human information processor. These stimuli are picked up by sensors like the eyes, ears, skin and the nose. The perceptual subsystem consists of these sensors, and associated buffer memories images collected by the sensors are temporarily stored in these buffer memories before they are passed on to the cognitive subsystem for processing.

The cognitive subsystem consists of a working memory or a short-term memory, a long-term memory and a cognitive processor.Shortly after sensory information is put into the sensory buffers by the sensors of the perceptual subsystem, the cognitive processor symbolically encodes the input and puts it into the working memory of the cognitive subsystem.The cognitive processor is like the central processing unit of a computer. It cycles periodically and recognizes that there is input in the sensory buffers that it needs to pick up and put in the working memory of the cognitive system.

The motor system is the final piece of the jigsaw puzzle, that is the human information-processing system. It is translated into action by motor processors which activate voluntary muscles which in turn results in some observable activity.

3. Expert systems

The basic structure of an expert system contains a knowledge base similar to the long-term memory of an expert, and it contains an inference mechanism that will pick up the appropriate information from the knowledge base like the cognitive processor in the human information processor. It has a working memory which holds the results of the last thought and the input that will trigger the next thought.

The knowledge base is made up of rules and facts much like the long-term memory of an expert. Representation of knowledge usually takes the form of rules operating on facts about objects of interest in the domain over which the expert system professes expertise.  

The second component of an expert system is the inference engine which operates on the knowledge base of the expert system in its search for a solution. The inference engine has two parts to it – the inference part and the control part. The inference engine handles incomplete information by allowing the rules to fail when information necessary to evaluate the premisses of these rules is not available.

This portion addresses two primary problems. First, an expert system must have a way to decide where to start. Rules and facts reside in the knowledge base. There must be a way for the reasoning process to begin. Second, the inference engine must resolve conflicts that occur when alternative lines of reasoning emerge. It could happen, for example, that the system reaches a point at which two or three rules can test to be true. The inference engine must choose which rule to examine next. 

Reference : 

Authors, F. (2005). New developments in computer software.