Type Annotation for Adaptive Systems
arXiv:1612.01637v1
Originality Synthesis-oriented
AI Analysis
This addresses typing limitations in adaptive systems, but appears incremental as it builds on existing graph-based approaches.
The paper tackles the problem of rigid typing in graph systems by introducing type annotations as a flexible alternative to classical graph morphisms, allowing elements to adapt to context changes.
We introduce type annotations as a flexible typing mechanism for graph systems and discuss their advantages with respect to classical typing based on graph morphisms. In this approach the type system is incorporated with the graph and elements can adapt to changes in context by changing their type annotations. We discuss some case studies in which this mechanism is relevant.