Fixed Point Theory is a beautiful mixture of analysis (pure and
applied), topology and geometry. Fixed point theorems give the
conditions under which mappings (single or multivalued) have solutions.
The fixed point theory in probabilistic metric spaces is useful in the
study of existence of solutions of operator equations in probabilistic
metric space and probabilistic functional analysis, which is a very
dynamic area of mathematical research. The notion of a probabilistic
metric space corresponds to the situations when we do not know exactly
the distance between two points; we know only probabilities of possible
values of this distance. This book contains six chapters. New fixed
point theorems for contraction mappings, expansion mappings,
probabilistic densifying mappings are obtained in Menger spaces. Also
related fixed point theorems in Menger spaces and applications of fixed
point theorems are studied. This book will help the researchers studying
fixed point theory.