AbstractGraphs of the single-step operator for first-order logic programs—displayed in the real plane—exhibit self-similar structures known from topological dynamics, i.e., they appear to be fractals, or more precisely, attractors of iterated function systems. We show that this observation can be made mathematically precise. In particular, we give conditions which ensure that those graphs coincide with attractors of suitably chosen iterated function systems, and conditions which allow the approximation of such graphs by iterated function systems or by fractal interpolation. Since iterated function systems can easily be encoded using recurrent radial basis function networks, we eventually obtain connectionist systems which approximate logic ...
AbstractOne facet of the question of integration of Logic and Connectionist Systems, and how these c...
Intelligent systems based on first-order logic on the one hand, and on artificial neural networks (a...
Recurrent neural networks can simulate any finite state automata as well as any multi-stack Turing m...
AbstractGraphs of the single-step operator for first-order logic programs—displayed in the real plan...
www.wv.inf.tu-dresden.de/∼{borstel,pascal} Graphs of the single-step operator for first-order logic ...
www.wv.inf.tu-dresden.de/∼{borstel,pascal} Graphs of the single-step operator for first-order logic ...
Graphs of the single-step operator for first-order logic programs—displayed in the real plane—exhibi...
We examine two connectionist networks—a fractal learning neural network (FLNN) and a Sim-ple Recurre...
Recent work by Siegelmann has shown that the computational power of recurrent neural networks matche...
One way to understand the brain is in terms of the computations it performs that allow an organism t...
"Artificial neural networks" provide an appealing model of computation. Such networks consist of an ...
We consider a model of so-called hybrid recurrent neural networks composed with Boolean input and ou...
One facet of the question of integration of Logic and Connectionist Systems, and how these can compl...
It has been known for a short time that a class of recurrent neural networks has universal computati...
We examine the approximating power of recurrent networks for dynamical systems through an unbounded ...
AbstractOne facet of the question of integration of Logic and Connectionist Systems, and how these c...
Intelligent systems based on first-order logic on the one hand, and on artificial neural networks (a...
Recurrent neural networks can simulate any finite state automata as well as any multi-stack Turing m...
AbstractGraphs of the single-step operator for first-order logic programs—displayed in the real plan...
www.wv.inf.tu-dresden.de/∼{borstel,pascal} Graphs of the single-step operator for first-order logic ...
www.wv.inf.tu-dresden.de/∼{borstel,pascal} Graphs of the single-step operator for first-order logic ...
Graphs of the single-step operator for first-order logic programs—displayed in the real plane—exhibi...
We examine two connectionist networks—a fractal learning neural network (FLNN) and a Sim-ple Recurre...
Recent work by Siegelmann has shown that the computational power of recurrent neural networks matche...
One way to understand the brain is in terms of the computations it performs that allow an organism t...
"Artificial neural networks" provide an appealing model of computation. Such networks consist of an ...
We consider a model of so-called hybrid recurrent neural networks composed with Boolean input and ou...
One facet of the question of integration of Logic and Connectionist Systems, and how these can compl...
It has been known for a short time that a class of recurrent neural networks has universal computati...
We examine the approximating power of recurrent networks for dynamical systems through an unbounded ...
AbstractOne facet of the question of integration of Logic and Connectionist Systems, and how these c...
Intelligent systems based on first-order logic on the one hand, and on artificial neural networks (a...
Recurrent neural networks can simulate any finite state automata as well as any multi-stack Turing m...