Learning Paradigm on English AI Terms Dictionary

Explanation-based learning

Sat, 18 Jul 2026 09:57:38 +0000

Definition

EBL combines symbolic reasoning with machine learning to accelerate the learning process. Instead of relying on large datasets, it takes a single positive example and uses a pre-existing domain theory to explain why the example belongs to the target concept. This explanation is then operationalized into a general rule that can be applied to future instances. It is particularly useful when data is scarce but domain knowledge is abundant, allowing for rapid acquisition of skills.

Data-driven model

Sat, 18 Jul 2026 09:52:47 +0000

Definition

A data-driven model is a type of artificial intelligence system where behavior and predictions emerge from patterns identified within historical data, rather than being defined by hard-coded rules or physical equations. Common examples include neural networks, decision trees, and regression models. These models excel in complex environments where the underlying mechanisms are unknown or too intricate to model analytically. Their effectiveness relies heavily on the volume, variety, and quality of the input data, making them central to modern machine learning applications in finance, healthcare, and autonomous systems.

zero-shot

Sat, 18 Jul 2026 09:39:43 +0000

Definition

Zero-shot learning enables models to generalize to new categories or tasks for which no labeled training data was provided during the initial training phase. This is typically achieved by leveraging semantic embeddings or textual descriptions that link known concepts to unknown ones. It is particularly powerful in large language models and multimodal systems, allowing for flexible adaptation to novel queries without retraining.

Summary

The ability to perform tasks on unseen classes without prior training examples.