Artificial Intelligence – Terminology
Artificial Intelligence is a study to make computers, robots, generally, machines think how the intellect of humans works, think, learn when it solves any problem. This will affect software systems that are more intelligent than usual. The main objective of Artificial Intelligence is to enhance computer functions that are related to natural knowledge, for illustration, logic, knowledge, and problem-answering.
The purposes of AI study are logic, knowledge representation, planning, knowledge, natural language processing, actualization, and the capability to move and manipulate objects. There are long-term intentions in the general intelligence sector. Approaches include statistical approaches, computational intelligence, and traditional coding AI. During the AI study related to hunting and precise optimization, artificial neural networks, and methodologies grounded on statistics, probability, and economics, we use numerous tools. Computer knowledge attracts AI in the field of science, mathematics, psychology, linguistics, philosophy, and so on.
List of frequently used terms in the domain of AI
Term | Meaning |
---|---|
Agent | Agents are systems or software programs suitable for self-governed, purposeful, and logic channeled towards one or another objective. They’re also called assistants, brokers, bots, droids, intelligent agents, and software agents. |
Automata theory | The study of abstract machines and automata, as well as the computational problems |
Autonomous Robot | The robot is independent of external control or influence and capability to govern itself solely. |
Autonomous car | A vehicle that is capable of sensing its environment and moving with little or no human input |
Backward Chaining | The scheme of working backward for the Reason/ effect of a problem. |
Blackboard | It’s the memory inside the computer, which is used for communication between the cooperating expert systems. |
Environment | It’s the part of the real or computational world inhabited by the agent. |
Forward Chaining | The strategy of working forward for the conclusion/ result of a problem. |
Heuristics | Knowledge is predicated on Trial-and-error, estimations, and experiments. |
Knowledge Engineering | Develops knowledge from natural experts and other sources. |
Percepts | It’s the format in which the agent obtains information about the surroundings. |
Pruning | Overriding nonessential and irrelative considerations in AI systems. |
Rule | It’s a format of representing knowledge base in Expert System. It’s in the form of IF-THEN-ELSE. |
Task | It’s the aim the agent is trying to achieve. |
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