AI: The Technological Trickster
By ai-depot | October 26, 2002
 Moving elegantly among social sciences, computational linguistics and classical AI disciplines, this article analyses the essence of computer thought compared to human reasoning, and emphasises its effects on society and future developments.
Moving elegantly among social sciences, computational linguistics and classical AI disciplines, this article analyses the essence of computer thought compared to human reasoning, and emphasises its effects on society and future developments.
Written by Jim Erkiletian.
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Moderating Online Chat Rooms
By ai-depot | October 24, 2002
 This paper shows how self-organised systems appear among chaos, given a nurturing environment. Such a technique is employed for self-moderation of message boards. Three types of moderation are discussed: automatic filtering, hierarchical censoring, and self-moderation through bottom-up feedback.
This paper shows how self-organised systems appear among chaos, given a nurturing environment. Such a technique is employed for self-moderation of message boards. Three types of moderation are discussed: automatic filtering, hierarchical censoring, and self-moderation through bottom-up feedback.
Written by Michael T. Pagano.
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Machine Learning in Games Development
By ai-depot | September 26, 2002
 Explains the current perceptions of ML in the games industry, some of the techniques and implementations used in present and future games. A description about designing your very own learning agent is provided.
Explains the current perceptions of ML in the games industry, some of the techniques and implementations used in present and future games. A description about designing your very own learning agent is provided.
Written by Nick Palmer.
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Color Recognition and Neural Networks
By ai-depot | September 18, 2002
 Demonstrates how to create a neural network that learns to classify patterns in colour components. The NN can thereby associate the concept of a `colour’ with different shades — a great example of the technology to pratical problems.
Demonstrates how to create a neural network that learns to classify patterns in colour components. The NN can thereby associate the concept of a `colour’ with different shades — a great example of the technology to pratical problems.
Written by James Kingsbery.
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Classical and Connectionist Cognitive Models
By ai-depot | September 2, 2002
 An introduction to the classical and connectionist classifications, discussing the advantages and disadvantages of each approach, and highlighting the difficulties faced in deciding which approach to adopt during development.
An introduction to the classical and connectionist classifications, discussing the advantages and disadvantages of each approach, and highlighting the difficulties faced in deciding which approach to adopt during development.
Written by Linden Hutchinson.
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