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Monday, 20 May 2013
 
 
 
AI Techniques for Machine Consciousness
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This section aims to cover the main Artificial Intelligence (AI) techniques that can be potentially used for Machine Consciousness.

Machine consciousness models are based on psychological or philosophical models. For the actual implementation of such systems several artificial intelligence techniques are generally applied. Here we try to review these AI techniques from the point of view of their application in the machine consciousness field.

Some of the areas related to this section are evolutionary computing, artificial neural networks, fuzzy logic, cognitive modeling, and computational perception.

 

  • Artificial General Intelligence  ( 2 items )

    As opposed to classical AI approaches where the whole research area is fragmented in narrow intelligent systems, the Artificial General Intelligence discipline aims to build an integrative alternative considering whole artificial systems that could develop intelligence parallel to that of humans.

  • Biologicaly Inspired AI  ( 1 items )

    This category covers all AI (Artificial Intelligence) techniques inspired in processes observed in biological organisms. Bio-inspired models are the foundation of many AI techniques like Artificial Neural Networks (ANN), Artificial Life (AL), Evolutionary Computing (EV), Swarm Intelligence (SI), etc.

  • Evolutionary Computing  ( 3 items )

    Evolutionary computing is one of the popular domains in the context of Artificial Intelligence tecniques. Here you will find articles related to the use of Genetic Programming (GP) and Genetic Algorithms in Machine Consciousness implementations.






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Machine Consciousness Bibliography Database

 

ConsScale
The Cognitive Machine Consciousness Scale

 
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