Aldebaran Nao Robot

In this article I aim to provide a comprehensive introduction to the field of cognitive robotics by providing you with some definitions, examples, links to information resources, courses, and research projects. Also, the research motivations of this field are discussed, as well as main application areas and the inspiration in natural cognitive systems.

The field of Cognitive Robotics is very much related with Machine Consciousness (MC). Indeed, I consider MC as a subfield or a specific focus of the research on Cognitive Robotics. Any implementation of the functionality of consciousness has to be framed within a cognitive architecture. Consciousness per se does not make any sense unless it is integrated in a subject able to develop end to end (embodied) processes like perception and behavior.

The ultimate aim of the development of cognitive architectures is the implementation of machines that are able to “know what they are doing”, thus being more robust, adaptive, and flexible. Social robots are significant example of the kind of applications that cognitive robots (and particularly conscious robots) might perform. Interacting with humans is an extremely complex task where all these cognitive capabilities are required.

Future cognitive robots are expected to be able to interact with humans, acting and learning in unpredictable environments.

Introduction to Cognitive Robotics (excerpt taken from [0])

Research in robotics has traditionally emphasized low-level sensing and control tasks including sensory processing, path planning, and manipulator design and control. In contrast, research in cognitive robotics is concerned with endowing robots and software agents with higher level cognitive functions that enable them to reason, act and perceive in changing, incompletely known, and unpredictable environments in a robust manner. Such robots must, for example, be able to reason about goals, actions, resources (linear and/or non-linear, discrete and/or continuous, replinishable or expendable), when to perceive and what to look for, the cognitive states of other agents, time, collaborative task execution, etc. In short, cognitive robotics is concerned with integrating reasoning, perception and action with a uniform theoretical and implementation framework.

The use of both software robots (softbots) and robotic artifacts in everyday life is on the upswing and we are seeing increasingly more examples of their use in society with commercial products around the corner and some already on the market. As interaction with humans increases, so does the demand for sophisticated robotic capabilities associated with deliberation and high-level cognitive functions. Combining results from the traditional robotics discipline with those from AI and cognitive science has and will continue to be central to research in cognitive robotics.

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Minority Report

At any given time the mind has to take decisions and multiple unconscious actions are done. Our conscious mind continuously confabulates making up the illusion that it is in charge. But, who is actually in charge?

Can science tell us what is exactly the human nature? Can we reproduce that in artificial machines? Consciousness and free will have been typically evading the scientific arena. However, in the latest decades, philosophers and scientists have begun to work together in the search for a scientific explanation of the mind. In a review of Dennett’s Book, Freedom Evolves [1], by Simon Blackburn [2], it is pointed out why scientists need philosophers. Libet’s experiments show that:

[…] neural activity that begins an action starts up around a third of second before the agent’s conscious decision to act.” […]

Usually, neuroscientists have interpreted this as the illusion of being in charge. Dennett supports that this is a mistaken view. Instead, a conscious agent must be seen as a continuum, where there is no single moment of decision. The interventionist conception deduced from Libet’s experiments usually lead scientists to think that evolution and culture have created a prison for the mind. Dennett argues the contrary, as he thinks evolution and culture are the key differentiators that make us humanly able to shape responses of reason and imagine the future. In relation with the link between thought and action:
“We have the power to veto our urges and then to veto our vetoes,” he said. “We have the power of imagination, to see and imagine futures.”  

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Strong AI

Is machine consciousness a key aspect of strong artificial intelligence (strong AI)?

Can machine consciousness be applied as a pragmatic approach in weak AI?

Are machine consciousness and strong AI the same thing?

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First of all, I would say that the concept of machine consciousness is not really new. What I think is new is the application of the latest scientific or philosophic models of consciousness in the Artificial Intelligence arena. Basically, machine consciousness central objective is to produce consciousness in an artificial system, and one of the greatest challenges here is to understand what actually a conscious process is. What we currently have is plenty of hypotheses which could be somehow applied to engineered artifacts. However, we don’t know to what extend these hypotheses correlate with the reality of human mind. This is the reason why we always keep a closer look to the latest advances in neuroscience. As the brain and cognitive sciences develop, more insight in the mind processes is gained.

There is no doubt that machine consciousness field has to be related to human consciousness studies (I’d better say scientific consciousness studies in general, as there are proofs of conscious behaviors in other mammals). Therefore, as part of the AI discipline, machine consciousness has to follow a multidisciplinary approach, where neuroscience, philosophy, psychology, physics, etc. All play a significant contribution role to the matter. Obviously, engineering play its central role here as well; at the end of the day, we are talking about machines.

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