Definition
In artificial intelligence and mathematics, ‘first-order’ typically describes systems or operations that involve direct, linear relationships without higher-order interactions. In optimization, it refers to methods using only gradient information (first derivative). In logic, first-order logic allows quantification over variables but not over predicates or functions. It contrasts with second-order or higher-order approaches that capture more complex dependencies.
Summary
Refers to concepts involving direct relationships or linear approximations, such as first-order logic or first-order derivatives.
Key Concepts
- Gradient descent
- First-order logic
- Linear approximation
- Derivatives
Use Cases
- Training neural networks via backpropagation
- Knowledge representation in symbolic AI
- Optimization algorithms like SGD