Title :
Participatory Learning With Granular Observations
Author :
Yager, Ronald R.
Author_Institution :
Iona Coll., Machine Intell. Inst., New Rochelle, NY
Abstract :
We introduce and discuss the participatory learning paradigm. A formal system implementing this type of learning agent is described. We then extend this system so that it can learn from interval-type observations. We further extend this system to the case when the observation is a more general granular object such as a fuzzy set. In the initial stage, while we allowed our observations to be granular, we restricted the learning to be precise values. In the next part, we allow both the observations and learned object to be granular. An important issue that arises when learning granular values relates to the specificity of the learned value. Learned values that are too unspecific can be useless. We suggest methods for controlling the specificity of the values learned.
Keywords :
fuzzy set theory; learning (artificial intelligence); multi-agent systems; fuzzy set theory; granular observation; learning agent; participatory learning paradigm; Fuzzy sets; learning; participatory learning paradigm (PLP); specificity; trapezoidal membership;
Journal_Title :
Fuzzy Systems, IEEE Transactions on
DOI :
10.1109/TFUZZ.2008.2005690