Artificial biochemical networks: A different connectionist paradigm

Christopher MacLeod, Niccolo F. Capanni

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Connectionist models are usually based on artificial neural networks. However, there is another route towards parallel distributed processing. This is by considering the origins of the intelligence displayed by the single celled organisms known as protoctists. Such intelligence arises by means of the biochemical interactions within the animal. An artificial model of this might therefore be termed an artificial biochemical network or ABN. This paper describes the attributes of such networks and illustrates their abilities in pattern recognition problems and in generating time-varying signals of a type which can be used in many control tasks. The flexibility of the system is explained using legged robots as an example. The networks are trained using back propagation and evolutionary algorithms such as genetic algorithms.

Original languageEnglish
Pages (from-to)123-134
Number of pages12
JournalArtificial Intelligence Review
Issue number1-2
Publication statusPublished - Feb 2010


  • Artificial neural network
  • Biochemistry
  • Connectionism
  • Evolutionary algorithm
  • Pattern recognition
  • Protein
  • Protozoa
  • Robot


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