Ecological modeling of human-machine interaction

Alex Kirlik

Research output: Contribution to journalConference articlepeer-review


An ecological approach to modeling human-machine interaction based on extensions of Brunswik's probabilistic functionalism is presented. The general approach is illustrated by a pair of quantitative models in dynamic, interactive task domains. The mathematical techniques used to instantiate the models include genetic algorithms (to describe noncompensatory-logical judgement rules), and multi-dimensional information theory (to describe how a performer generates perceptual information through action, thereby reducing a task's cognitive demands). The models indicate how Brunswik's probabilistic functionalism, previously applied mainly to the analysis of passive judgement, can be extended to the realm of dynamic, interactive tasks. The style of ecological analysis and description portrayed in these models is especially well suited to describing types of, and limits to, adaptation in human-machine interaction.

Original languageEnglish (US)
Pages (from-to)I-732 - I-737
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
StatePublished - 1999
Externally publishedYes
Event1999 IEEE International Conference on Systems, Man, and Cybernetics 'Human Communication and Cybernetics' - Tokyo, Jpn
Duration: Oct 12 1999Oct 15 1999

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture


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