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Artificial Intelligence is the study related to intelligent agent. This is a mechanical device which is used to analyze the environment & scan actions which maximize relative chances of attaining success towards the pre-defined goals & objectives. Under this subject, you have to learn of many different approaches of Artificial Intelligence like statistical methods, computational intelligence, traditional symbolic Artificial Intelligence and many more. It is evident that the study of artificial intelligence is complex & challenging in many aspects.
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Research Goals Covered In Artificial Intelligence
We know that Artificial Intelligence gets the credit of bringing in many innovations with respect to the method & way of how machines function. This has also improved & changed the amount of time required to complete certain tasks by the humans. This particular field is further divided into different sub-fields & covers many concepts which are extremely important to understand the related complexities.
Scientists make use of Artificial Intelligence tools & try to achieve research goals such as reasoning, problem-solving. There are many computational problems under this aspect & they form an integral part of the subject like probability & economics as well.
- Problem Solving & Reasoning: Here, different computational problems like probability & economics are taken into consideration & are worked upon.
- Representation of Knowledge: This is known to be one of the most important & core element of Artificial Intelligence. It covers all the knowledge related to the world with prime focus on certain real world situations like events, states & semantics of a particular issue.
- Planning: This deals with the state of world around you & makes certain predictions about actions which might account to change them in any way.
- Learning: This particular concept of machine learning is used to study computer algorithms which help in improving the functionality of machine automatically through effective use of experience.
- Natural Language Processing: This enables a machine to understand & interpret along with read the human language with ease.
- Perception: This helps you analyze the visual input by using censors. It is also applied in different areas like facial recognition, speech recognition & also object recognition.
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- The Real World
- Representation Of Knowledge
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- Probablistic Reasoning
- Knowledge In Learning
- Probablistic Models
- Reinforcement Learning
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