Taskdependent

Taskdependent, or task-dependent, is an adjective used to describe properties, effects, or representations that vary with the task being performed. It denotes that a feature or outcome depends on the specific requirements, goals, or context of the task rather than being universal across tasks.

In cognitive science and neuroscience, task dependence describes how neural representations and behavioral strategies can change with different objectives. For example, the same sensory input might elicit different patterns of brain activity when a person is asked to categorize stimuli versus detect their presence, reflecting task-dependent encoding and processing.

In machine learning and artificial intelligence, task-dependent models learn representations that are tailored to a particular objective. Features or embeddings optimized for one task (such as sentiment analysis) may differ from those optimized for another task (such as topic classification). This contrasts with task-agnostic approaches that aim to perform well across multiple tasks, often using transfer learning or multi-task training to bridge task gaps.

In robotics and automation, control policies, planners, and perception pipelines can be task-dependent because different tasks impose distinct performance criteria, constraints, or safety requirements. Task dependence affects evaluation, generalization, and the need for task analysis during system design.

Overall, recognizing task dependence helps in designing, evaluating, and generalizing systems by clarifying which properties are expected to vary with the task and which are intended to be task-invariant. See also task-specific, task-agnostic, generalization, and transfer learning.