Pentti O. A. Haikonen

Consciousness and robot sentience

The Real Problem of Consciousness Consciousness and Subjective Experience Perception and Qualia From Perception to Consciousness Emotions and Consciousness Inner Speech and Consciousness Qualia and Machine Consciousness Testing Consciousness Artificial Conscious Cognition Associative Information Processing Neural Realization of Associative Processing Designing a Cognitive Perception System Examples of Perception/Response Feedback Loops The Transition to Symbolic Processing Information Integration with Multiple Modules Emotional Significance of Percepts The Outline of the Haikonen Cognitive Architecture (HCA) Mind Reading Applications The Comparison of Some Cognitive Architectures Example: An Experimental Robot with the HCA Concluding Notes Consciousness Explained.

QUALIA AND CONSCIOUS MACHINES

It is argued that qualia are the primary way in which sensory information manifests itself in mind. Qualia are not seen as properties of the physical world, ready to be observed; instead it is argued that they are the way in which the sensory systems response to the sensed stimuli manifests itself inside the system. Systems that have qualia have direct and transparent access to this response. It is argued that even though qualia are produced inside the head, they appear to be outside because this appearance complies with our motions, small and large, in the word. To be conscious in the way that we experience it is to have qualia. True conscious machines must have qualia, but the qualities of machine qualia need not be similar to the qualities of human qualia.

The Role of Associative Processing in Cognitive Computing

The traditional approaches—of symbolic artificial intelligence (AI) and of sub-symbolic neural networks—towards artificial cognition have not been very successful. The rule-based symbolic AI approach has proven to be brittle and unable to provide any real intelligence (Mckenna, Artificial intelligence and neural networks: steps toward principled integration, Academic Press, USA, 1994). On the other hand, traditional artificial neural networks have not been able to advance very much beyond pattern recognition and classification. This shortcoming has been credited to the inability of conventional artificial neural networks to handle syntax and symbols. Hybrid approaches that combine symbolic AI and sub-symbolic neural networks have been tried with results that fall short of the ultimate goal. It has been argued that traditional AI programs do not operate with meanings and consequently do not understand anything (Searle, Minds, brains & science, Penguin Books Ltd, London, 1984; Searle, The mystery of consciousness, Granta Books, London, 1997). It seems that in this way some essential ingredient is missing, but there may be a remedy available. Associative information processing principles may enable the utilization of meaning and the combined sub-symbolic/symbolic operation of neural networks.

XCR-1: An Experimental Cognitive Robot Based on an Associative Neural Architecture

The experimental cognitive robot XCR-1 is a small three-wheel robot with gripper hands, multiple sensory modalities, and self-talk. The robot XCR-1 is designed for studies and experiments with a new paradigm for cognitive computation, namely an associative neural processing style that inherently and seamlessly combines sub-symbolic and symbolic computation. This operation is realized by using associative neurons and neuron groups organized according to the Haikonen Cognitive Architecture. Recently, there have been many efforts toward machine consciousness, and the Haikonen Cognitive Architecture is one attempt in that direction. Human consciousness is characterized by subjective inner experience that is related to qualia. Accordingly, it can be proposed that true conscious machines should also have some kind of inner experience and qualia. On the other hand, it has been argued that qualia are direct and cannot be artificially realized in symbolic systems. In order to facilitate qualia-related practical investigations, the robot XCR-1 utilizes direct perception processes, with dedicated hardware and without symbolic pre-programmed algorithms. The robot XCR-1 does not utilize microprocessors or programs of any kind. Natural language is one manifestation of symbolic processing. The robot XCR-1 is designed also for experiments with simple speech and the basic grounding of the meaning of words. The experiments with the robot XCR-1 could be greatly enhanced if dedicated associative neuron group chips were available.

Yes and No: Match/Mismatch Function in Cognitive Robots

Abstract Associative match, mismatch and novelty detection is an essential function in human and artificial cognition and is related to perception, reasoning and emotion. In the human brain, match/mismatch-related and novelty-detection-related signals and states can be detected by EEG and more advanced imaging technologies. Match, mismatch and novelty detection should also be present in artificial cognitive architectures that seek to provide a framework for artificial cognition, especially for autonomous robots. Here, the functions of match, mismatch and novelty are discussed, their implementation in one artificial cognitive architecture (HCA) is described and their application in the robot XCR-1 is given as a practical example.

CONSCIOUSNESS AND SENTIENT ROBOTS

It is argued here that the phenomenon of consciousness is nothing more than a special way of a subjective internal appearance of information. To explain consciousness is to explain how this subjective internal appearance of information can arise in the brain. To create a conscious robot is to create subjective internal appearances of information inside the robot. Other features that are often attributed to the phenomenon of consciousness are related to the contents of consciousness and cognitive functions. The internal conscious appearance of these is caused by the mechanism that gives rise to the internal appearances in the first place. A useful conscious robot must have a variety of cognitive abilities, but these abilities alone, no matter how advanced, will not make the robot conscious; the phenomenal internal appearances must be present as well. The Haikonen Cognitive Architecture (HCA) tries to facilitate both internal appearances and cognitive functions. The experimental robot XCR-1 is the first implementation experiment with the HCA.

Quasi-Quantum Computing in the Brain?

Quantum computing has been seen as a potentially powerful computing method, and consequently some researchers have argued that the brain might somehow utilize quantum computing processes. In the laboratory, quantum computing calls for exotic conditions, and it has been argued that the brain cannot provide these. Here, a novel computing method, quasi-quantum computing, is presented. This method utilizes the main principles of quantum computing: superposition, entanglement and collapse, but in this case, computing is not based on quantum processes; instead, it is realized by utilizing conventional electronic devices in rather unconventional ways. As an example of the potential of this approach, the reverse computing of mathematical functions is considered, and an experimental test device is reported. Some aspects of this approach may be used by the brain as no exotic conditions are required. However, further research would be required.

Consciousness and the Quest for Sentient Robots

Existing technology allows us to build robots that mimic human cognition quite successfully, but would this make these robots conscious? Would these robots really feel something and experience their existence in the world in the style of the human conscious experience? Most probably not. In order to create true conscious and sentient robots we must first consider carefully what consciousness really is; what exactly would constitute the phenomenal conscious experience. This leads to the investigation of the explanatory gap and the hard problem of consciousness and also the problem of qualia. This investigation leads to the essential requirements for conscious artifacts and these are: 1.) The realization of a perception process with qualia and percept location externalization, 2.) The realization of the introspection of the mental content, 3.) The reporting allowed by seamless integration of the various modules and 4.) A grounded self-concept with the equivalent of a somatosensory system. Cognitive architectures that are based on perception/response feedback loops and associative sub-symbolic/symbolic neural processing would seem to satisfy these requirements.

Towards associative non-algorithmic neural networks

A novel associative artificial neuron together with pulse train signals is proposed for the building block for non-algorithmic neural networks. These neurons operate on signal with inherent meaning and they may easily be cross connected and cascaded for various functions such as Pavlovian conditioning and concept/feature detectors. Short term and long term memory functions are also easily implemented and are in many circuits inherent.<<ETX>>

MACHINE CONSCIOUSNESS: NEW OPPORTUNITIES FOR INFORMATION TECHNOLOGY INDUSTRY

New product and system opportunities are expected to arise when the next step in information technology takes place. Existing Artificial Intelligence is based on preprogramed algorithms that operate in a mechanistic way in the computer. The computer and the program do not understand what is being processed. Without the consideration of meaning, no understanding can take place. This lack of understanding is seen as the major shortcoming of Artificial Intelligence, one that prevents it to achieve its original goal; thinking machines with full human-like cognition and intelligence. The emerging technology of Machine Consciousness is expected to remedy this shortcoming. Machine Consciousness technology is expected to create new opportunities in robotics, information technology gadgets and general information processing calling for machine understanding of auditory, visual and linguistic information.