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Some questions involve projects that the candidate has worked on in the past. A coding interview is intended to seek out creative thinkers and those who can adapt their solutions to rapidly changing and dynamic scenarios. [citation needed] Typical questions that a candidate might be asked to answer during the second-round interview include: [7]
Calling a problem AI-complete reflects the belief that it cannot be solved by a simple specific algorithm. In the past, problems supposed to be AI-complete included computer vision, natural language understanding, and dealing with unexpected circumstances while solving any real-world problem. [2] AI-complete were notably considered useful for ...
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]
Means–ends analysis [1] (MEA) is a problem solving technique used commonly in artificial intelligence (AI) for limiting search in AI programs.. It is also a technique used at least since the 1950s as a creativity tool, most frequently mentioned in engineering books on design methods.
It is seen as the canonical NP-complete problem. Although no known algorithm is known to solve SAT in polynomial time, there are classes of SAT problems which do have efficient algorithms that solve them. The classes of problems amenable to SAT heuristics arise from many practical problems in AI planning, circuit testing, and software verification.
Parallel problem solving: mainly deals with how classic artificial intelligence concepts can be modified, so that multiprocessor systems and clusters of computers can be used to speed up calculation. Distributed problem solving (DPS): the concept of agent , autonomous entities that can communicate with each other, was developed to serve as an ...
Robot in a wooden maze. A maze-solving algorithm is an automated method for solving a maze.The random mouse, wall follower, Pledge, and Trémaux's algorithms are designed to be used inside the maze by a traveler with no prior knowledge of the maze, whereas the dead-end filling and shortest path algorithms are designed to be used by a person or computer program that can see the whole maze at once.
The key role of AI in collaborative intelligence was predicted in 2012 when Zann Gill wrote that collaborative intelligence (C-IQ) requires “multi-agent, distributed systems where each agent, human or machine, is autonomously contributing to a problem-solving network.” [6] Gill’s ACM paper has been cited in applications ranging from an ...