Guiding Probabilistic Logical Inference with Nonlinear Dynamical Attention Allocation

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8598)


In order to explore the practical manifestations of the “cognitive synergy” between the PLN (Probabilistic Logic Networks) and ECAN (Economic Attention Network) components of the OpenCog AGI architecture, we explore the behavior of PLN and ECAN operating together on two standard test problems commonly used with Markov Logic Networks (MLN). Our preliminary results suggest that, while PLN can address these problems adequately, ECAN offers little added value for the problems in their standard form. However, we outline modified versions of the problem that we hypothesize would demonstrate the value of ECAN more effectively, via inclusion of confounding information that needs to be heuristically sifted through.


Test Problem Logic Network General Intelligence Markov Logic Network VLDB Endowment 
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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.OpenCog FoundationHong Kong
  2. 2.Novamente LLCUSA
  3. 3.Adams State UniversityUSA
  4. 4.iCog LabsHong Kong
  5. 5.School of DesignHong Kong Poly UHong Kong
  6. 6.University of WashingtonUSA

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