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Haikonen's comment on article by Doan
Written by Pentti Haikonen   
Wednesday, 16 December 2009

Pentti Haikonen comments invited by Conscious-Robots.com editor on the recent article about Haikonen's Architecture for Conscious Machines written by Trung Doan.

I wish to thank Trung Doan for his analysis of my approach towards machine consciousness here. Trung Doan has done a lot of work here as he illustrates the main principles with practical examples, which are worked out along the principles that I present in my book "Robot Brains".

Pentti Haikonen
Dr. Haikonen
I would like to add some comments. My realization relies on associative neurons, which form associative memories. An associative memory is a rather old invention, but it has not gained much popularity because of the so-called interference problem, which limits the capacity of the memory. My contribution relates to the interference problem and in my book I describe methods, which allow the interference-free use of the full capacity; the capacity of the associative memory can be the same as the capacity of similar complexity random access memory. However, if only partial capacity is used, then the associative memory also performs the act of classification.

Trung Doan notes correctly that the neural machinery does not operate with numeric values, instead the individual signals represent elementary features of sensed entities and these are the basic meaning of these signals. It is useful to note that in the machinery groups of signals that represent some sensed entity may be used to stand for completely different things; these signal groups act as symbols for these things. This is a necessary prerequisite for e.g. natural language and inner speech.

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Last Updated ( Thursday, 17 December 2009 )
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Pentti Haikonen's architecture for conscious machines
Written by Trung Doan   
Thursday, 10 December 2009

Pentti Haikonen's architecture for conscious machines

By Trung Doan (doanviettrung a_t gmail dot com). 

Haikonen's contribution to the machine-consciousness endeavor is an architecture based on cognitive principles. He also developed some electronic microchips as a first step to building a machine based on that architecture.

Below, we look at how a Haikonen machine might achieve consciousness once built, by examining some of its cognitive capabilities, and in the process will briefly discuss the Haikonen architecture.

The Haikonen machine perceives

Say the Haikonen machine's cameras are  focusing on a yellow ball. The cameras' pixel pattern is fed into a preprocessor circuit which produces an array of, say, 10,000 signals, each signal carried by, for example, a wire. One wire is the output from the preprocessor's "roundness" circuitry and, in this case, the signal is On. Another wire, from the "squareness" circuitry, would be Off, i.e. carrying no voltage. A group of wires is the output from the spectrum-analysis circuitry, the wire corresponding to frequencies which we humans recognise as "yellow" is On while "red", "blue", etc., wires are Off. There would be many other groups of wires depicting size, brightness, edges, etc.

The machine does not internally represent the ball as a round graphic, nor a set of numbers representing diameter, color, etc., but by this signal array. Haikonen calls this a "distributed signal representation".

Suppose the machine is shown several balls of different sizes, colors, etc., one at a time, and each time its microphone hears the sound pattern we humans understand as the word "ball". Because they appear at the same time repeatedly, the machine associates the sound pattern and the visual pattern together. The making of associations is how the machine's perception is done.

After several different balls are associated with that sound pattern, the machine finally learns to associate the "ball" sound pattern with anything that is round.

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Last Updated ( Friday, 11 December 2009 )
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Journal of Mind Theory
Written by Raúl Arrabales Moreno   
Friday, 20 November 2009

Journal of Mind Theory Journal of Mind Theory

Rigor in Cognitive Science

The UPM Autonomous Systems Lab (AsLab) has recently launched a new journal in the field of congnitive science. The focus of the new Journal of Mind Theory (JMT) is on precise, succinct, non-interpretable theories of hypotheses on the nature of the mind. The journal is edited by Ricardo Sanz and Jaime Gómez, and the editorial board includes well known experts in the fields of cognitive science and machine consciousness.

This journal tries to capture the formal science of mind, attempting to pursue the ultimate goal of a unified formal theory of mind, but open to any proposal and not tied to a specific language.

The first two numbers of the JMT are alredy online (including papers from James Albus, Ron Cottan, Pentti Haikonen, Konrad Talmont-Kaminski, Andrée C. Ehresmann, Tariq Samad, Lorenzo Magnani, Sarah Rebecca, and others) :

- JMT Vol. 0. No. 1.
- JMT Vol. 0. No. 2.

 

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Last Updated ( Friday, 20 November 2009 )
 
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