Artificial Intelligence and Soft Computing: Behavioral ... - Arteimi.info

which, however, is not presented here to maintain continuity of the present
context.
The microscopic view of the three common vesicular aggregates, studied
by Lahiri [3], is presented below. It demonstrates that the 2-D spatial
periodicity
DMPC = Dimyristoyl phosphatidylcholine
Fig. 13.8: Digitized images for the vesicular clusters made by (a) DMPC,
(b) DMPC in presence of spectrin and (c) a mixed lipid system
made by DMPC and cholesterol, obtained from a Phase Contrast
Microscope.
(structural repetitiveness) of the texture of these vesicular clusters has
considerable differences in microscopic observation, and as a consequence
their classification from 2-D features is feasible. A non-linear 2-D
classification of these three vesicular aggregates has been presented in fig.
13.9. It is observed from the figure that the boundaries of the classes (b) and
(c) have a small separation, while that of (a) & (b), and (a) & (c) have a large
spatial gap. The results also intuitively follow from the microscopic view.
Not only in Biology, but in almost every branch of Science, pattern
classification is of immense importance. In Psychology, for example, pattern
classification is used to classify people of different mental diseases for
treatment by a common therapy. In criminology the fingerprint of a suspect is
classified into typical classes prior to matching it with known fingerprint
databases of that class. Whatever be the problem, the main task in pattern
classification is to extract the features, for which no automated methods is
known to date.
13.4 Reinforcement Learning
In reinforcement learning, the learner adapts its parameters by determining the
status (reward / punishment) of the feedback signal from its environment. The