Self-Improvement
The capability of an AI system to iteratively enhance its performance or reasoning using its own outputs, feedback, or data.
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Related terms
A learning approach in which an AI system continuously updates its behavior or model using newly available data during operation.
Continual LearningA learning approach in which an AI system continuously acquires new knowledge and skills over time while retaining previously learned capabilities.
Reinforcement LearningRLA machine learning paradigm where an agent learns to make optimal decisions by taking actions in an environment to maximize cumulative rewards.
Preference LearningA learning approach in which an AI system learns from preferences between possible outputs or actions to better align its behavior with desired outcomes.
Fine-tuningThe process of further training a pretrained AI model on a task-specific or domain-specific dataset to improve its performance, behavior, or specialization for particular use cases.
Adaptation PolicyA set of rules or strategies that governs how an AI agent adjusts its behavior, plans, or parameters in response to changing conditions or feedback.