Modeling brain function—the world of attractor neural networks
Modeling brain function—the world of attractor neural networks
Distributed Representations, Simple Recurrent Networks, And Grammatical Structure
Machine Learning - Connectionist approaches to language learning
From complexity to creativity: explorations in evolutionary, autopoietic, and cognitive dynamics
From complexity to creativity: explorations in evolutionary, autopoietic, and cognitive dynamics
The basins of attraction of a new Hopfield learning rule
Neural Networks
Creating Internet Intelligence: Wild Computing, Distributed Digital Consciousness, and the Emerging Global Brain
The Architecture of Cognition
Godel, Escher, Bach: An Eternal Golden Braid
Godel, Escher, Bach: An Eternal Golden Braid
Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
Building Large Knowledge-Based Systems; Representation and Inference in the Cyc Project
An Overview of Hybrid Neural Systems
Hybrid Neural Systems, revised papers from a workshop
A fast learning algorithm for deep belief nets
Neural Computation
Probabilistic Logic Networks: A Comprehensive Framework for Uncertain Inference
Probabilistic Logic Networks: A Comprehensive Framework for Uncertain Inference
Neural-Symbolic Cognitive Reasoning
Neural-Symbolic Cognitive Reasoning
Perspectives of Neural-Symbolic Integration
Perspectives of Neural-Symbolic Integration
Proceedings of the 2007 conference on Advances in Artificial General Intelligence: Concepts, Architectures and Algorithms: Proceedings of the AGI Workshop 2006
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
Probabilistic logic networks in a nutshell
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
| Hi-index | 0.01 |
The concept of glocal memory (i.e. memory involving systematic coordination between localized memory traces and globalized dynamical-attractor-based memory traces) is reviewed, and is argued to be a critical principle for the design of artificial brains and artificial general intelligence systems. Some exploratory experiments are reviewed, involving introduction of glocal memory into Hopfield neural networks, and also into economic attention networks as utilized in the OpenCog and Novamente integrated AI architectures.