Universal Artificial Intelligence: Sequential Decisions Based On Algorithmic Probability
Universal Artificial Intelligence: Sequential Decisions Based On Algorithmic Probability
Extending the Soar Cognitive Architecture
Proceedings of the 2008 conference on Artificial General Intelligence 2008: Proceedings of the First AGI Conference
Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning
Implementing First-Order Variables in a Graphical Cognitive Architecture
Proceedings of the 2010 conference on Biologically Inspired Cognitive Architectures 2010: Proceedings of the First Annual Meeting of the BICA Society
Factor graphs and the sum-product algorithm
IEEE Transactions on Information Theory
Deconstructing reinforcement learning in sigma
AGI'12 Proceedings of the 5th international conference on Artificial General Intelligence
Extending mental imagery in sigma
AGI'12 Proceedings of the 5th international conference on Artificial General Intelligence
Modeling two-player games in the sigma graphical cognitive architecture
AGI'13 Proceedings of the 6th international conference on Artificial General Intelligence
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This article describes the extension of a memory architecture that is implemented via graphical models to include core aspects of problem solving. By extensive reuse of the general graphical mechanisms originally developed to support memory, this demonstrates how a theoretically elegant implementation level can enable increasingly broad architectures without compromising overall simplicity and uniformity. In the process, it bolsters the potential of such an approach for developing the more complete architectures that will ultimately be necessary to support autonomous general intelligence.