Objective: This article presents a systematic framework characterizing adaptive systems.
Background: Adaptive systems are those that can appropriately modify their behavior to fit the current context. This concept is appealing because it offers the possibility of creating computer assistants that behave like good human assistants who can provide what is needed without being asked. However, the majority of adaptive systems have been experimental rather than practical because of the technical challenges in accurately perceiving and interpreting users' current cognitive state; integrating cognitive state, environment, and task information; and using it to predict users' current needs. The authors anticipate that recent developments in neurological and physiological sensors to identify users' cognitive state will increase interest in adaptive systems research and practice over the next few years.
Method: To inform future efforts in adaptive systems, this work provides an organizing framework for characterizing adaptive systems, identifying considerations and implications, and suggesting future research issues.
Results: A two-part framework is presented that (a) categorizes ways in which adaptive systems can modify their behavior and (b) characterizes trigger mechanisms through which adaptive systems can sense the current situation and decide how to adapt.
Conclusion: The framework provided in this article provides a tool for organizing and informing past, present, and future research and development efforts in adaptive systems.