This book is written for computer engineers, scientists, and students studying/working in
reinforcement learning and artificial intelligence domains. The book collects recent …

Shortest path problem in stochastic graphs has been recently studied in the literature and a
number of algorithms has been provided to find it using varieties of learning automata …

A fusion of learning automata and Petri nets, referred to as APN-LA, has been recently
introduced in the literature for achieving adaptive Petri nets. A number of extensions to this …

Grid computing, in simplest terms, is distributed computations that have reached higher
evolution level. Grid scheduler is part of Grid. Scheduler generates an assignment of jobs to …

In a Petri net, a decision point is raised when two or more transitions are simultaneously
enabled in a given marking. The decision to be made at such a point is the selection of an …

Evolvable hardware (EHW) deals with the application of evolutionary algorithms in hardware
design. In intrinsic EHW, the evolutionary algorithm or the fitness evaluation is implemented …

The CLA-EC is a model obtained by combining the concepts of cellular learning automata
and evolutionary algorithms. The parallel structure of the CLA-EC makes it suitable for …

Cellular automata (CA) have been shown to be suitable for modelling and simulating
complex adaptive systems. To achieve adaptation to the exterior environment, Learning …

Image segmentation is an important task in image processing and computer vision which
attract many researchers attention. There are a couple of information sets pixels in an image …

Many optimization problems in real world are dynamic in the sense that the global optimum
value and the shape of fitness function may change with time. The task for the optimization …