Personal profile

Research interests

  1. Cognitive architectures: I develop the CHREST model of human learning and perceptual expertise.
  2. Data mining: algorithms and applications in text and image analysis.
  3. Methodology: techniques and tools to aid in the development of scientific models and software.


Peter Lane has degrees in Mathematics and Computer Science.  His research interests cover many aspects of machine learning and its applications, including the simulation of human learning.  His early work looked at connectionist models of natural-language learning.  More recently, he has worked on the CHREST cognitive architecture of human perception and learning.  His current project uses genetic programming to develop cognitive models from psychological data.


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Collaborations and top research areas from the last five years

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