Behavioral Learning Theory
The theory that all behaviors are acquired through conditioning, often used to understand and influence behavior change.
The theory that all behaviors are acquired through conditioning, often used to understand and influence behavior change.
A phenomenon where people are more likely to remember information when they are in the same state of consciousness as when they learned it.
ModelOps (Model Operations) is a set of practices for deploying, monitoring, and maintaining machine learning models in production environments.
The process of self-examination and adaptation in AI systems, where models evaluate and improve their own outputs or behaviors based on feedback.
A theoretical approach that focuses on observable behaviors and dismisses internal processes, emphasizing the role of environmental factors in shaping behavior.
Volatility, Uncertainty, Complexity, and Ambiguity (VUCA) is an acronym for describing the challenging conditions of the modern world.
A practice of performing testing activities in the production environment to monitor and validate the behavior and performance of software in real-world conditions.
A temporary increase in the frequency and intensity of a behavior when reinforcement is first removed.
A logical fallacy where people assume that specific conditions are more probable than a single general one.