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Pronounced "A-star". A graph traversal and pathfinding algorithm which is used in many fields of computer science due to its completeness, optimality, and optimal efficiency. abductive logic programming (ALP) A high-level knowledge-representation framework that can be used to solve problems declaratively based on abductive reasoning. It extends normal logic programming by allowing some ...
Although AI seems to be evolving rapidly, it faces many technical challenges. For example, in many cases the language used by AI is very vague, and thus confusing for the user to understand. In addition, there is a "black-box problem" [11] [10] in which there is a lack of transparency and interpretability in the language of AI outputs. In ...
Prolog is particularly useful for symbolic reasoning, database and language parsing applications. Artificial Intelligence Markup Language (AIML) [11] is an XML dialect [12] for use with Artificial Linguistic Internet Computer Entity (A.L.I.C.E.)-type chatterbots. Planner is a hybrid between procedural and logical languages. It gives a ...
Generative artificial intelligence (generative AI, GenAI, [1] or GAI) is a subset of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. [ 2 ] [ 3 ] [ 4 ] These models learn the underlying patterns and structures of their training data and use them to produce new data [ 5 ] [ 6 ] based on ...
Prompt engineering is the process of structuring or crafting an instruction in order to produce the best possible output from a generative artificial intelligence (AI) model. [ 1 ] A prompt is natural language text describing the task that an AI should perform. [ 2 ]
Natural language understanding (NLU) or natural language interpretation (NLI) [1] is a subset of natural language processing in artificial intelligence that deals with machine reading comprehension. NLU has been considered an AI-hard problem.
Given that an AI does not inherently have language, it is unable to think about the meanings behind the words of a language. An artificial notion of meaning needs to be created for a strong AI to emerge. [3] Creating an artificial representation of meaning requires the analysis of what meaning is. Many terms are associated with meaning ...
The idea of creation of artificial language arose in 17th and 18th century as a result of gradually decreasing international role of Latin. [1] The initial schemes were mainly aimed at the development of a rational language free from inconsistence of living language and based on classification of concepts.