Behaviour of Artifical Intelligence

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1. INTRODUCTION
Artificial intelligence is defined as two different entities that adjoined take on a completely different perspective. Defining artificial as something created or built by a human action or influence for use and artificial behaviour is seen as insincere. Intelligence is defined as the ability to gather, understand and then appropriately use the information and further broaden knowledge. Artificial intelligence together is identified as a ‘theory’ in which computers or machines are able to perform tasks normally undertaken requiring human intelligence. Visual perception, recognition of speech, language translation and decision-making are certain tasks that can be completed.
2. SWARM INTELLIGENCE
Swarm intelligence is the developing collective intelligence of simple agent groups, it is a type of artificial intelligence and its purpose is to simulate behaviour of social insects or swarms. A swarm is seen as a structure collection of interacting agents but technically is considered to be decentralised self-organised systems. As an example an ant colony foraging in which all agents (ants) interact as a self-organised system knowing their individual roles. Individually ants are unable to solve complex problems which they may face whereas colonies collectively can solve complex problems such as identifying the nearest source of food. Swarm intelligence results in actions that are coordinated without any coordinator or external controller.
Natural systems exhibiting swarm intelligence is a colony of ants similar to a flock of birds or a herd of animals as they all move together in groups and are behaviourally distinct. Even though individual behaviour is distinct the group members have the ability to act in unanimity. Th...

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...conducted to identify whether these would be successful. At this stage the conflict resolutions during the air traffic control process are mostly theoretical.
5. CONCLUSION
In conclusion the implementation of ACO to air traffic control does have advantages and limitations as ants search for the shortest path for the source of food correlates to aircrafts trying to reach their destination. ACO can be successful in air traffic control as it allows for error correction, removal of conflict zones and improving journey speed. There are also constraints as this concept is not 100% accurate but with the flexibility of ACO it has the ability to react to any possible problems and then adequately assign a solution. Although aircraft risk is greater than those of ants there is plausible evidence given that the implementation of ACO for air traffic control will be a success.

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