Letter perception: from pixels to pandemonium.

Perception, Logic and Action through Structured Motivated Associative Pandemonium

The Pandemonium Association Engine (PAE) [5,2,6] is proffered in an attempt to fulfil the cognitive necessities of an agent embodying true intelligence and common sense, and hopefully helping unify the main cognitive paradigms. The operation of the basic model and the performance of the second stage of development introducing imaginary concepts and goals are outlined, along with the principles ...

The pandemonium system of reflective agents

The Pandemonium system of reflective MINOS agents solves problems by automatic dynamic modularization of the input space. The agents contain feedforward neural networks which adapt using the backpropagation algorithm. We demonstrate the performance of Pandemonium on various categories of problems. These include learning continuous functions with discontinuities, separating two spirals, learning...

Session 3 Paper 6 Pandemonium : a Paradigm for Learning

Multi Agent Systems meet Pandemonium

AKIRA is an open-source framework integrating MAS and Pandemonium features. Here we discuss AKIRA’s peculiarities and compare it with some of the most known MAS platforms. We show how to use AKIRA for Agent based modeling, providing some examples. We also describe a client-server scheme allowing for a kind of ‘middleware’, e.g. an AI server for game actors, intelligent tutoring systems, or deci...

The RGF pandemonium: a low-level representational model for images

In this work, we have reformulated the selection of a few responding units tuned to patterns of activity from the Fourier spectrum as a multilayer system composed of four stages of di erent kinds of feature detectors. The system output is a sparse representation for images that produces an organization according to object power discrimination. The resultant multilayer system provides a more e c...