Computational intelligence approaches are nature-inspired methods, which offer a wealth of ideas for solutions to complex problems. In comparison to the traditional approaches, the computational intelligence approaches are more powerful so that they do not need the reformulation of the problem to search a nonlinear and a nondifferentiable space with real world conditions with the massive parall...

Artificial Intelligence is the intelligence of machines focusing on creating machines that can engage on behaviors that human considers Intelligent Expert Systems are the programs based on their theory and methods of AI. Expert Systems have a wide variety of applications especially when coming to object recognition. This paper explains the applications of expert systems in object recognition an...

Artificial Intelligence focuses on the question of how to design systems to exhibit intelligent behaviour in complex environments. Complex global behaviours can emerge from simple systems acting in a complex environment; however, this emergence requires that the systems’ internal structure reflect essential structures in the environment. This paper examines the algebraic structure of a system’s...

Artificial Intelligence (AI) textbooks and research papers often discuss the big questions, such as "how to reason with uncertainty," "how to reason efficiently", or "how to improve performance through learning." It is more difficult, however, to find descriptions of concrete problems or challenges that are still ambitious and interesting, yet not so open-ended. This paper analyzes the measurin...

Artificial Intelligence focuses on the question of how to design systems to exhibit intelligent behaviour in complex environments. Complex global behaviours can emerge from simple systems acting in a complex environment; however, this emergence requires that the systems’ internal structure reflect essential structures in the environment. This paper examines the algebraic structure of a system’s...

Several methods are employed in multi-agent learning and organization problem such as temporal difference (TD(λ)), genetic algorithms, and learning classifier systems. The main disadvantage of these methods is that they perform badly when the data is not fully observable. In this paper, we first introduce explain learning systems in artificial intelligence(AI) and Self-organization systems. The...

The design of future air traffic management (ATM) systems appears as a grand challenge. Because of its very large scale, complexity, and dynamicity, we believe that the future of air traffic management lies in hybrid distributed cooperative control systems, including human experts (air traffic controllers) and also intelligent computer support through artificial agents. Such artificial agents c...

Recently, computational agents received significant attention in computer science research community. In fact, intelligent agents is a powerful artificial intelligence technology showing considerable promise as a new paradigm for mainstream software development and able to offer new ways of abstraction, decomposition, and organization that fit well with our natural view of the world. However, d...