Artificial Intelligence‌ Artificial Sample Clauses

Artificial Intelligence‌ Artificial. Intelligence (AI) is a field with a surprisingly long history, arguably dating back almost a millennium, with the first search algorithm being developed by the great philosopher and xxxxxxxx Xxx Xxxx (known in western culture by his Latinized name, Xxxxxxxx) [68]. Known mostly for his work on medicine, metaphysics and ethics, he was also a logician, with new translations of his work revealing a proof search algorithm for syllogisms. It can be considered telling that the field that was born in the middle of the Islamic Golden Age, a time that greatly evolved human thought, has been uncovered and brought to the forefront in the late 20th/early 21st century, as both eras led to unprecedented growth and prosperity. However, both periods had to navigate the huge disruptions in their societies and divisions in their populations. AI in the 1950s and 1960s was described by Xxxxxx Xxxxxx [99] as being split into five major areas: Search, Pattern Recognition, Learning, Planning and Induction. During this period, XX was envisioned as a symbolic-based general problem and theorem solver. This is nowadays referred to as Good Old Fashioned Artificial Intelligence (GOFAI) [58], in contrast to the more data-driven approaches that are now popular. Most modern AI systems are now characterised and described based on the environment present and the agents affecting it [124]. This thesis focuses on the area of AI that Xxxxxx referred to as Planning, which is the discipline tasked with making agents reason about sequential decision-making problems – which actions they should take so that they can achieve a desired state, while taking into account their intended and unintended consequences [94, 119]. From an engineering point of view, we define Planning as a system that, when tasked with a complex problem, will produce a sequence of actions that can achieve the intended goal by combining work from several fields, such as knowledge representation, heuristic search, inferences, model abstraction, monotonic/non-monotonic logic, etc.
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