Adaptivity

Adaptivity is the property of a system to modify its behavior, structure, or parameters in response to changes in its environment or goals. This adjustment is typically achieved through feedback, monitoring, and learning mechanisms that enable the system to perform better under varying conditions.

In engineering and computer science, adaptive systems use sensors and models to select actions or tune control parameters. Examples include adaptive control where controller gains adjust in real time, adaptive mesh refinement in numerical simulations, and adaptive bitrate streaming that responds to network conditions.

In education and psychology, adaptive approaches tailor instruction or interventions to an individual's knowledge, skills, or state using assessments and learner models.

In data science and machine learning, adaptivity describes algorithms that update their behavior as new data arrive (online learning) and methods to handle concept drift.

In biology and ecology, adaptivity relates to an organism's capacity for plasticity and behavioral change; long-term adaptivity can involve evolutionary processes.

Assessment and design considerations include stability and safety, avoiding overfitting or oscillations, managing data and computational requirements, and balancing responsiveness with robustness.

Distinctions exist between adaptivity and related terms: adaptivity is the capacity or process, while adaptability describes the overall ability to adjust, and adaptiveness is a noun form used in some disciplines.