Design for a Darwinian Brain: Part 2. Cognitive Architecture

  • Chrisantha Fernando
  • Vera Vasas
  • Alexander W. Churchill
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8064)


The accumulation of adaptations in an open-ended manner during lifetime learning is a holy grail in reinforcement learning, intrinsic motivation, artificial curiosity, and developmental robotics. We present a design for a cognitive architecture that is capable of specifying an unlimited range of behaviors. We then give examples of how it can stochastically explore an interesting space of adjacent possible behaviors. There are two main novelties; the first is a proper definition of the fitness of self-generated games such that interesting games are expected to evolve. The second is a modular and evolvable behavior language that has systematicity, productivity, and compositionality, i.e. it is a physical symbol system. A part of the architecture has already been implemented on a humanoid robot.


Actor Molecule Humanoid Robot Motor Command Salient Object Cognitive Architecture 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Chrisantha Fernando
    • 1
  • Vera Vasas
    • 1
  • Alexander W. Churchill
    • 1
  1. 1.Dept. of Electronic Engineering and Computer ScienceQueen Mary University of LondonUK

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