Discover published sets by community

Data structures representing stereotypical situations with slots to fill in properties or attributes. Example: A frame for 'House' with slots for 'color', 'size', and 'number of rooms'.

Also known as Bayesian Networks, they are graphical models representing probabilistic relationships among variables. Example: A network representing the probability of 'Rain' given the presence of 'Clouds'.

Condition-action pairs used in rule-based systems. Example: IF 'traffic light is red' THEN 'stop the car'.

A graphical representation of knowledge based on nodes representing concepts and edges representing relationships. Example: A node for 'Bird' with an edge labeled 'is-a' connected to another node for 'Animal'.

A family of formal knowledge representation languages used for ontologies. Example: Using concepts, roles, and individuals to define a 'Person' who 'hasChild' some 'Individual'.

Search algorithms based on the mechanics of natural selection and genetics. Example: Optimizing a function by evolving a population of candidate solutions.

Systems that apply rules to a knowledge base to infer new information or make decisions. Example: A medical diagnosis system that uses rules like, IF 'symptom A' and 'symptom B' THEN 'disease X'.

A formal representation of a set of concepts within a domain and the relationships between them. Example: Concepts like 'Person', 'Company', and 'Job' with relationships like 'works at' and 'owns'.

A problem-solving technique that reuses past experiences to find solutions to new problems. Example: Diagnosing a patient based on similar previous cases.

A strategy to deal with uncertainty by making presumptions when no information to the contrary is known. Example: Assuming a bird flies unless it is known that it does not.

Computational models inspired by the human brain that are used for pattern recognition. Example: A multi-layer network trained to recognize handwritten digits.