# IEE Colloquium on Symbols Versus Neurons

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Displaying Results 1 - 11 of 11
• ### Artificial intelligence for genomic interpretation

Publication Year: 1990, Page(s):11/1 - 11/4
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Biological entities present a complexity level that should be correctly managed in Artificial Intelligence environments. One has to describe and access them in a proper way. What is the role of symbolic learning in this context? The authors define semi-empirical knowledge and theories, which constitute their goals. Knowledge is represented by the means of conceptual graphs, which allow one to mana... View full abstract»

• ### Subsymbolic inductive learning framework for large-scale data processing

Publication Year: 1990, Page(s):10/1 - 10/8
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Recent years have witnessed the development of a large variety of Inductive methods for data analysis. This can be attributed to the fact that the decision tree-the most common representation of Inductive algorithms-provides a hierarchical framework for sequential decision making. This is a framework which non-professionals find easy to use and understand. Furthermore, it has been proved that Indu... View full abstract»

• ### Real time reinforcement learning control of dynamic systems applied to an inverted pendulum

Publication Year: 1990, Page(s):7/1 - 7/2
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Describes work started in order to investigate the use of neural networks for application in adaptive or learning control systems. Neural networks have learning capabilities and they can be used to realize non-linear mappings. These are attractive features which could make them useful building blocks for non-linear adaptive or learning controllers View full abstract»

• ### Using the genetic algorithm to adapt intelligent systems

Publication Year: 1990, Page(s):4/1 - 4/4
Cited by:  Papers (2)
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The genetic algorithm, loosely based on the mechanics of evolution, is used in machine learning and optimisation problems that typically have a large search space and require a high tolerance to noise. Two examples are given of its use in the learning of rules for real-time control problems; one for adaptive rule-based optimisation of combustion in multiple-burner installations in the steel indust... View full abstract»

• ### A systolic algorithm for back-propagation: mapping onto a transputer network

Publication Year: 1990, Page(s):2/1 - 2/4
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The paper is devoted to the implementation of Back-Propagation (BP) on local memory multiprocessor systems (LMM). First, a systolic algorithm (SA) is described, where dependencies are considered at the data item level. Next, the systolic array is partitioned and mapped onto a multiprocessor system. At this stage, the level of granularity is increased, in order to reduce communication cost. Finally... View full abstract»

• ### IEE Colloquium on Symbols Versus Neurons' (Digest No.123)

Publication Year: 1990
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The following topics were dealt with: knowledge and machine architecture; systolic algorithms for back-propagation; connectionism; genetic algorithms; neural networks and MIMD-multiprocessors; real-time reinforcement learning control; relational and differential logic for knowledge processing; constraint-based reasoning in Pandora; subsymbolic inductive learning framework; genomic interpretation; ... View full abstract»

• ### Inductive protein structure analysis (IPSA)

Publication Year: 1990, Page(s):12/1 - 12/7
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The current state of protein structure analysis and prediction methods shows three important points. First, classical methods of secondary structure prediction cannot solve the protein folding problem; secondly, a combination of classical method returns better results for the prediction of secondary structures than any one of the methods on its own; and thirdly, methods that try to incorporate the... View full abstract»

• ### Symbolic constraint-based reasoning in Pandora

Publication Year: 1990, Page(s):9/1 - 9/5
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Introduces an intelligent programming technique to adopt constraint-based reasoning in Pandora: a non-deterministic parallel logic programming language. The technique is illustrated in solving resource allocation problems, such as automatically generating naval flying programmes View full abstract»

• ### Neural networks and MIMD-multiprocessors

Publication Year: 1990, Page(s):511 - 514
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Two artificial neural network models are compared. They are the Hopfield neural network model and the Sparse Distributed Memory model. Distributed algorithms for both of them are designed and implemented. The run time characteristics of the algorithms are analyzed theoretically and tested in practise. The storage capacities of the networks are compared. Implementations are done using a distributed... View full abstract»

• ### Connectionism-a link between psychology and neuroscience?

Publication Year: 1990, Page(s):3/1 - 3/7
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Neural network' or connectionist models are currently `in' in psychology and cognitive science. Why is this so? The author of this paper thinks that one important reason for this is the hope of many psychologists and cognitive scientists that by using such models the gap between theories of the mind and behavior on the one hand and theories of the brain on the other hand could be made narrower. I... View full abstract»

• ### Knowledge and machine architectures

Publication Year: 1990, Page(s):1/1 - 1/9
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A paradigm is proposed based upon a taxonomy of knowledge; a taxonomy that has been strongly influenced by the need to represent knowledge for machine processing. The importance of such a paradigm is to show an equivalence of activity in all spheres of system design from knowledge systems to machine architectures and thus open up the possibility of cross fertilization of techniques and a redistrib... View full abstract»