The central problems (or goals) of AI research include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects.^[6] General intelligence is still among the field's long-term goals.^[7] Currently popular approaches include statistical methods, computational intelligence and traditional symbolic AI. There are a large number of tools used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics, and many others. The AI field is interdisciplinary, in which a number of sciences and professions converge, including computer science, mathematics,psychology, linguistics, philosophy and neuroscience, as well as other specialized fields such as artificial psychology.https://www.youtube.com/watch?v=on-0PYf-m9s

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                            include statistical methods, computational intelligence and traditional symbolic AI. There are a large number of tools used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics, and many others. The AI field is interdisciplinary, in which a number of sciences and professions converge, including computer science, mathematics,psychology, linguistics, philosophy and neuroscience, as well as other specialized fields such as artificial psychology.https://www.youtube.com/watch?v=on-0PYf-m9s