9618 · 18.1
Artificial Intelligence (AI) flashcards
Revision flashcards for Cambridge 9618 Artificial Intelligence (AI) (syllabus 18.1). Flip, recall, then mark a real past-paper question.
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Artificial Intelligence (AI)
The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
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Expert System
A computer system that emulates the decision-making ability of a human expert in a narrow, specific domain. It uses a knowledge base of facts and rules.
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Knowledge Base
A component of an expert system containing the facts and the rule base (IF-THEN rules) for a specific knowledge domain.
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Inference Engine
The 'brain' of an expert system. It applies logical rules from the knowledge base to the facts of a case to deduce new information and arrive at a conclusion.
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Machine Learning (ML)
A subset of AI where algorithms are trained on data to learn patterns and make predictions or decisions, without being explicitly programmed for the task.
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Supervised Learning
A type of machine learning where the algorithm learns from a dataset that has been manually labelled with the correct outputs. It learns a mapping from input to output.
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Unsupervised Learning
A type of machine learning where the algorithm learns from an unlabelled dataset, identifying hidden patterns or structures within the data on its own (e.g., clustering).
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Reinforcement Learning
A type of machine learning where an 'agent' learns to behave in an environment by performing actions and seeing the results (rewards or penalties).
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Artificial Neural Network (ANN)
A computational model inspired by the structure and function of biological neural networks in the brain. It consists of interconnected nodes (neurons) in layers.
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Deep Learning
A subfield of machine learning based on artificial neural networks with many layers (deep neural networks). It is particularly effective for learning complex patterns from large datasets.
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Turing Test
A test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. A human evaluator judges natural language conversations between a human and a machine.
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Forward Chaining
An inference engine strategy that starts with the available data (facts) and uses inference rules to extract more data until a goal is reached.