Cognition and Consciousness. Retecog Summer School 2012

“Cognition and Consciousness” Retecog Summer School 2012

5-8 June 2012, Menorca, Spain.

Invited Lecturers: Kevin O’Regan, Anil Seth, Ap Dijsterkuis & Arne Öhman.


The Retecog Network fosters interdisciplinary collaboration to promote the advancement of Cognitive Science in Spain. This summer school aims to offer an overview of research in Cognitive Science through the choice of an area of research which provides a clear demonstration of the potential benefits of multidisciplinary cross-fertilization. It is addressed to graduate students, or recent doctors, interested in gaining a broader view of their research topic, and benefit from interdisciplinary collaboration. Participants are expected to present their current projects, either as poster or oral presentation, and will be offered feedback and further support.


The Summer School is addressed primarily to graduate students and recent doctors related to the groups that constitute the Retecog network. They will have their travel and accommodation expenses covered. Number of places is 25. Non-members of the network can also apply; they will just have the accommodation covered.


Contact toni dot gomila -at- uib dot cat before the end of April.

Tutorials will be offered by members of Retecog.Net. They will be introductory, 2-hour sessions, which will provide a quick access to a specific problem related to consciousness. Each student will be able to choose 6, among a those offered. At this moment, confirmed tutorials are:

Antoni Gomila: “Consciousness: why it matters”
Oscar Vilarroya: “Unity of consciousness”
Fernando Martínez-Manrique/Agustín Vicente: “Language and consciousness”
Ricardo Sanz: “Computational models of consciousness”
Raul Arrabales: “Machine consciousness”
Antoni Rodríguez-Fornells: “Unconscious control in the brain”
Miguel A. Salichs: “Perception and Consciousness”
Nacho Serrano: “Methodological problems in the study of consciousness”
Juan González: “Altered states of consciousness”
Xabier Barandiaran: “Subjecting consciousness: habits, habitat and sensorimotor subject”


CFP: Advances in Cognitive and Emotional Information Processing (ACEIP)

Call for Papers
Advances in Cognitive and Emotional Information Processing (ACEIP)

 Submissions are invited for a special session on Advances in Cognitive and Emotional Information Processing (ACEIP) to be held within the 2012 International Symposium on Neural Networks (ISNN), taking place from 11th to 14th July in Shenyang (China).

Cognitive and Emotional Information Processing techniques have encountered a large success within the scientific community, specially due to the impact they naturally have in diverse application fields as commerce, tourism, education and health. A wide number of advanced solutions have been proposed on purpose spanning from User/Web Interfaces and Mobile Computing to Robotics, Ambient Intelligence, and Computer Support to Collaborative Work/Learning. The objective is devoted to adequately interpret humans’ opinions, tastes and needs and consequently provide not only useful direct feedback to them but also a valid and natural support to the interactions they can have between themselves and with smart cooperative environments. This asks for development of expert systems, able to manage large amount of information coming from sensory activity, to intelligently process it, and to promptly and knowledgeably respond to human actions according to natural interaction standards and by means of suitable actuary devices. Information processing therefore plays a central role from this perspective, operating at different levels, from multimodal digital data manipulation to semantic metadata processing, and necessarily encompassing the most challenging computational intelligence paradigms for contextual adaptation, social-emotional competence, and cognitive reasoning abilities. Moreover, if on one hand the distillation of knowledge from such type data is a key factor for most of the applications it must be also said on the other hand that the extremely unstructured nature of these contents and their exponentially growing size make it a very difficult task to be faced. Information scientists working in related areas such as multimedia, machine learning, knowledge management, affective computing or semantic web are invited to contribute to attain the above research aims, by sharing their expertise in this emerging interdisciplinary field, and at the same time paving the way to new exciting research topics in the cognitive and emotional information processing field.

Topics of interest include but are not limited to:
•  Socio-Emotional Data Processing Techniques and Applications
•  Human Behaviour Analysis and Understanding
•  Cognitive Systems for Multimodal Interaction
•  Cognitive-Emotional Models in Cooperative Scenarios
•  Computational Intelligence Techniques for Affective Computing
•  Semantic Information Processing
•  Multimedia-interfaced Systems for Human-Machine Interaction

•  February 15th, 2012: Due date for Special Session papers
•  April 1st, 2012: Notification of paper acceptance to authors
•  May 1st, 2012: Camera-ready of accepted papers
•  July 11th, 2012: Special Session date

Prospective authors are invited to submit full-length papers (6-8 pages normally and 10 pages maximum) by the submission deadline through the online submission system. The submission of a paper implies that the paper is original and has not been submitted under review or copyright protected elsewhere and will be presented by an author if accepted. All submitted papers will be refereed by experts in the field based on the criteria of originality, significance, quality, and clarity. The authors of accepted papers will have an opportunity to revise their papers and take consideration of the referees’ comments and suggestions. All papers accepted by and presented at BICS 2012 will be published by Springer as multiple volumes of Lecture Notes in Artificial Intelligence which will be indexed by EI and ISTP. Selected papers will be published in special issues of several SCI journals.

•  Stefano Squartini, Marche Polytechnic University (Italy)
•  Erik Cambria, National University of Singapore (Singapore)
•  Francesco Piazza, Marche Polytechnic University (Italy)
•  Bjoern Schuller, Technical University of Munich (Germany)

For up-to-date information about this CFP, please visit

Retecog 2011 – The Architectures of Mind

ReteCog.Net 2011 Workshop
The Architectures of Mind

Workshop ReteCog.Net 2011: The architectures of Mind
Dates: 4-6 July
Venue: ASLab, Madrid, Spain

ReteCog 2011 is centered around the major topic of COGNITIVE ARCHITECTURE. Unveiling the architecture of the mind is a cornerstone of all our research programmes. The workshop aims to bring together leading scholars, scientists and engineers who use analytic and synthetic methods both to understand the astonishing processing properties of biological systems, specifically those of the living brain, and to exploit such knowledge to advance engineering methods for building artificial systems with higher levels of cognitive competence.

ReteCog 2011 is a meeting point of mind theorists, cognitive systems engineers and brain scientists where cross-domain ideas are fostered in the hope of getting new emerging insights on the nature, operation and extractable capabilities of brains and minds. This multiple approach is necessary because the progressively more accurate data about brains is producing a growing need of both a quantitative and deep theoretical understanding and an associated capacity to manipulate these data and translate it into engineering applications rooted in sound theories. ReteCog 2011 is intended for both i) life scientists who use and develop mathematical and engineering approaches for a better, system-level understanding of the cognitive behavior of complex biological systems and ii) technology researchers that aim to understand and build systems with higher cognitive competences. ReteCog 2011 is organized to foster collaboration patterns that encourage cross-fertilization across the workshop domains topics. This emphasizes the role of as a major meeting point for researchers and practitioners in the areas of natural and artificial cognitive systems.

Debates across disciplines will enrich researchers with complementary perspectives from diverse scientific fields. To help in this direction of tight interaction, the workshop will accept a maximum of 50 communications.

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Sackler Centre for Consciousness Science

The Sackler Centre for Consciousness Science (SCCS) at the University of Sussex has been recently founded

SCCS web site: 

Founded in 2010 with a generous donation from the Mortimer and Theresa Sackler Foundation, the Sackler Centre for Consciousness Science (SCCS) represents a new and multidisciplinary approach to clinical intervention and diagnosis, based on the science of the complex brain networks that give rise to consciousness.

How do conscious experience, subjectivity and free will arise from their biological substrates? Even in the late 20th century, consciousness was considered by many to be outside the reach or remit of science. Now, powerful new combinations of functional brain imaging, computational modelling and basic neurobiology bring real hope that human ingenuity can resolve this central mystery of life. Practically, an enhanced understanding of consciousness will transform clinical approaches to a wide range of neurological and psychiatric disorders, from coma to insomnia, from depression and schizophrenia to autism and dementia.


How to Make a Robot that Feels

How to Make a Robot that Feels

This article is divided in two parts:

  1. A summary of Kevin O’Regan keynote talk at CogSys 2010 by Raúl Arrabales.
  2. An invited extended discussion about the self and the role of action in sensation by Kevin O’Regan.

How to Make a Robot that Feels

strong_robot“How to make a robot that feels” was the title of the keynote talk given by Kevin O’Regan at the CogSys 2010 conference last week. During this talk O’Regan introduced the so-called hard problem of consciousness (as coined by Chalmers) and explained his sensorimotor approach to (phenomenal) consciousness [1]. This talk and related ideas are of special interest for Machine Consciousness researchers since O’Regan offers an account for sensory feel which virtually eliminates the hard problem, and therefore the explanatory gap itself. In the following I will try to summarize the key ideas that I got from both the talk and further discussions we had with O’Regan during the CogSys conference.

Using the redness of red, quite typical example in philosophy of mind, O’Regan addressed the problem of designing a robot that feels. Note that in this context the word feel is not used as in Damasio’s work, but to refer to the what-is-it-like or qualia associated to conscious contents, i.e. sensory feel.

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Can a robot pass the mirror test?

awarerobot_zoomFirst of all, the mirror test is not exactly intended as a general test for consciousness, but a specific test for self-consciousness, and more exactly self-recognition. It is generally applied to some higher mammals and infants. The test consists on determining whether or not the subject can recognize its own reflection in a mirror. So far, only subjects belonging to the following species have passed the mirror test:

humans (over 2 years old),
great apes (bonobos, chimps, orangutans, and gorillas),
rhesus monkeys,
bottlenose dolphins,
and octopuses.

I think it is important to note that only a determined number of individuals of these species have passed the tests, while others generally fail to pass it. Obviously the test has to be adapted to each specie, although it typically consists on an odorless paint mark made in the forehead while the animal is anesthetized.

The mirror test has been considered by some researchers as one of the best available ways to test self-consciousness in organisms (see for instance how it is applied to Elephants in [1], and see [2] for an open discussion about the mirror test validity). Mirror test is famous thanks to its application to primates, as introduced by Gordon Gallup in the 70’s [3]. However, little work has been done in the application of the mirror test to robots.

Can we build a robot able to successfully pass the mirror test? And if so, does it really mean that the robot is self-aware?

Takeno et al. [4] at Meiji University in Japan claim that they have succeeded in achieving mirror image cognition for a robot. They define four steps for their experiments, where four robots are used: the self robot Rs, the other robot Ro, the controlled robot Rc, and the automatic robot Ra. The first two robots are endowed with the mirror image cognition system. The third robot is controlled by the self robot, while the last one moves automatically.

The four experiments are as follows:

1) The self robot Rs imitates the action of its own image reflected in a mirror.
2) The self robot Rs imitates an action taken intentionally by the other robot Ro as imitative behavior.
3) The controlled robot Rc is controlled completely from the self-robot to imitate his behavior.
4) The self robot Rs imitates the random actions of the automatic robot Ra.

The robot is able to recognize its own image reflected in a mirror without confusing it with the image of another robot with the same physical aspect. The mirror image cognition system is based on an artificial neural network. The aim of this system is to recognize and differentiate robot’s own behavior from other robot’s behavior. Takeno also suggests that imitation is a proof of consciousness as it requires the recognition of other subject’s behavior and then the application of that behavior to oneself.

The results described in the paper indicate that in some way the robots are passing the mirror test with an accuracy of 70%, but I am reluctant to claim that they are self-conscious. I would rather say that the present a-consciousness of their recognized image.

[3] Gallup, G.G., Jr. (1977). Self-recognition in primates: A comparative approach to the bidirectional properties of consciousness. American Psychologist, 32, 329-337.
[4] Junichi Takeno, Keita Inaba, Tohru Suzuki. Experiments and examination of mirror image cognition using a small robot. Proceedings. 2005 IEEE International Symposium on Computational Intelligence in Robotics and Automation, 2005. CIRA 2005. Full paper available at:

Haikonen’s comment on article by Doan

Pentti Haikonen comments invited by 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”.

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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Pentti Haikonen’s architecture for conscious machines

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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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.