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Knowledge representation and reasoning (KRR, KR&R, or KR²) is a field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can use to solve complex tasks, such as diagnosing a medical condition or having a natural-language dialog.
His research is in the area of knowledge representation and reasoning in artificial intelligence.On the representation side, he has worked on the formalization of a number of concepts pertaining to artificial and natural agents including belief, goals, intentions, ability, and the interaction between knowledge, perception and action.
In artificial intelligence, symbolic artificial intelligence (also known as classical artificial intelligence or logic-based artificial intelligence) [1] [2] is the term for the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of problems, logic and search. [3]
Watson also has the capacity for knowledge representation and reasoning, which is essentially learning by context and employing language flexibility, like the intellectual flexibility needed in ...
A frame language is a technology used for knowledge representation in artificial intelligence. They are similar to class hierarchies in object-oriented languages although their fundamental design goals are different. Frames are focused on explicit and intuitive representation of knowledge whereas objects focus on encapsulation and information ...
The Loom project's goal is the development and fielding of advanced tools for knowledge representation and reasoning in artificial intelligence. Specifically to enable code to be generated from provably valid domain models. Loom is a language and environment for constructing intelligent applications.
Former OpenAI chief scientist Ilya Sutskever, one of the biggest names in artificial intelligence, had a prediction to make on Friday: reasoning capabilities will make technology far less predictable.
Chapter 2 A Representation and Reasoning System forward and backward chaining Chapter 3 Using Definite Knowledge includes databases and natural language Chapter 4 Searching includes standard state space searches, dynamic programming, constraint satisfation, hill climbing, "randomization algortihms" and genetic algorithms
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