Definition
The term ‘driven’ is commonly used as a suffix to indicate the primary force or mechanism behind an AI approach. For instance, ‘data-driven’ implies decisions are made based on statistical patterns in data rather than explicit programming, while ‘goal-driven’ suggests actions are optimized to maximize a specific reward signal, as seen in reinforcement learning. It highlights the foundational paradigm of the system, distinguishing between rule-based logic and emergent behaviors derived from inputs or optimization targets.
Summary
Driven describes AI systems or methodologies where decision-making or model architecture is primarily guided by a specific input type, such as data or objectives.
Key Concepts
- Data-Centric Approach
- Objective Optimization
- Paradigm Identification
- Reinforcement Learning
Use Cases
- Describing data-centric AI workflows
- Defining reinforcement learning agents as goal-driven
- Classifying hybrid systems as knowledge-driven or data-driven