Indefinite Probabilities for General Intelligence
Proceedings of the 2007 conference on Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms: Proceedings of the AGI Workshop 2006
Probabilistic Quantifier Logic for General Intelligence: An Indefinite Probabilities Approach
Proceedings of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference
Nonlinear-dynamical attention allocation via information geometry
AGI'11 Proceedings of the 4th international conference on Artificial general intelligence
OpenPsi: realizing Dörner's "Psi" cognitive model in the OpenCog integrative AGI architecture
AGI'11 Proceedings of the 4th international conference on Artificial general intelligence
Three hypotheses about the geometry of mind
AGI'11 Proceedings of the 4th international conference on Artificial general intelligence
AGI'11 Proceedings of the 4th international conference on Artificial general intelligence
Probabilistic logic networks in a nutshell
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
Inductive Logic Programming and Embodied Agents: Possibilities and Limitations
International Journal of Agent Technologies and Systems
A vision for a stochastic reasoner for autonomic cloud deployment
Proceedings of the Second Nordic Symposium on Cloud Computing & Internet Technologies
Integrating deep learning based perception with probabilistic logic via frequent pattern mining
AGI'13 Proceedings of the 6th international conference on Artificial General Intelligence
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This book describes Probabilistic Logic Networks (PLN), a novel conceptual, mathematical and computational approach to uncertain inference. In order to carry out effective reasoning in real-world circumstances, AI software must robustly handle uncertainty. However, previous approaches to uncertain inference do not have the breadth of scope required to provide an integrated treatment of the disparate forms of cognitively critical uncertainty as they manifest themselves within the various forms of pragmatic inference. Going beyond prior probabilistic approaches to uncertain inference, PLN is able to encompass within uncertain logic such ideas as induction, abduction, analogy, fuzziness and speculation, and reasoning about time and causality. The book reviews the conceptual and mathematical foundations of PLN, giving the specific algebra involved in each type of inference encompassed within PLN. Inference control and the integration of inference with other cognitive faculties are also briefly discussed.