Decision making soft computing agents
The paper describes a soft computing agent approach to intelligent control of remote learning. It presents a special type of decision making soft computing agent applied to the selection of appropriate groups for definition of individual remote learning purposes. Soft computing agents are used to perform two tasks: optimal partitioning of distributed data bases in accordance with a grade of ability, and coordination in distributed environment for remote group definition. The first task is realized via two-hierarchical fuzzy system for optimisation of assessment parameters. The second is achieved by means of mobile intelligent agents for transmission, coordination, activation, and receiving decisions from/to remote learning nodes. As a final decision the node soliciting optimal group choice obtains information for group distributions over the whole system. This approach is applied in some cases to disabled people suffering from dyslexia. Dyslexia is defined as a learning disability by four psychologically obtained factors that present the grade of learning deficiency. They are preliminary provided for better understanding and formalisation of remote learning process applied to disable people.
soft computing agent remote learning learning ability partitioning in groups