informationprocessinglike

Informationprocessinglike is a term used to describe phenomena, models, or systems that resemble information processing in structure or function. It denotes a likeness to the canonical information processing framework, where inputs are perceived, encoded, stored, transformed, and output as actions or decisions. The phrase signals that a process is similar to classical information-processing accounts without asserting exact equivalence.

The term is a neologism formed from information processing and the suffix -like. It appears in scholarly writing to indicate resemblance rather than full adherence to traditional information-processing explanations. In this sense, informationprocessinglike descriptions can apply to a range of domains where symbolic manipulation, representation, and rule-based transformation play a role, even when other factors are also present.

Applications and examples include cognitive science and artificial intelligence contexts where architectures imitate sequential or parallel information handling. Symbolic processing systems, cognitive architectures such as ACT-R, and certain rule-based or hybrid models are described as informationprocessinglike. Some discussions of neural networks emphasize both information-processinglike aspects (transformation of inputs into representations and outputs) and their distributed, non-symbolic features.

Key features often associated with informationprocessinglike accounts include inputs, encoding into representations, memory stores, transformations or computations, decision rules, output, and feedback or learning mechanisms. This framing supports modular, pipeline-like analyses but may be combined with broader methodological approaches, such as connectionist or dynamical perspectives.

See also:

- Information processing theory

- Symbolic AI

- Cognitive architecture

- ACT-R

- SOAR

- Connectionism

- Dynamical systems theory

- Embodied cognition