large-scale projects to build artificial brains: abaccus. włodzisław duch (google: duch)...

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  • Slide 1
  • Large-scale projects to build artificial brains: ABACCUS. Wodzisaw Duch (Google: Duch) Department of Informatics, Nicolaus Copernicus University, Torun, Poland School of Computer Engineering, Nanyang Technological University (NTU), Singapore Building Artificial Brain workshop after ICANN 2005, Sept 15, 2005
  • Slide 2
  • Attention-Based Artificial Cognitive Control Understanding System (ABACCUS) Large EU integrated project (>150 pp), with 9 participants: Kings College London (John G. Taylor, coordinator), UK Kings College London (John G. Taylor, coordinator), UK Centre for Brain & Cognitive Development, Berkbeck College, University of London, UK Centre for Brain & Cognitive Development, Berkbeck College, University of London, UK Cognition and Brain Sciences Unit, Medical Research Council, UK Cognition and Brain Sciences Unit, Medical Research Council, UK Robotics and Embedded Systems, Technical University of Munich, G Robotics and Embedded Systems, Technical University of Munich, G Institute of Neurophysiology and Pathophysiology, Universittsklinikum Hamburg-Eppendorf, G Institute of Neurophysiology and Pathophysiology, Universittsklinikum Hamburg-Eppendorf, G Institute of Computer Science, Foundation for Research and Technology Hellas, Heraklion, Crete, GR Institute of Computer Science, Foundation for Research and Technology Hellas, Heraklion, Crete, GR National Center for Scientific Research Demokritos, Athens, GR National Center for Scientific Research Demokritos, Athens, GR Dipartimento di Informatica, Sistemistica, Telematica, Universita di Genova, I Dipartimento di Informatica, Sistemistica, Telematica, Universita di Genova, I Dep. of Informatics, Nicholaus Copernicus University, Torun, PL Dep. of Informatics, Nicholaus Copernicus University, Torun, PL Now changed to Brain as Complex System (BRACS)
  • Slide 3
  • ABACCUS Goals Assumption: gross neuroanatomical brain structure is critical for its function, therefore it should be preserved.Assumption: gross neuroanatomical brain structure is critical for its function, therefore it should be preserved. To demonstrate how fusion of the appropriate brain-based models, guided by the overall architecture of the brain, and by its developmental learning stages, can help attain high-level cognitive processing capabilities.To demonstrate how fusion of the appropriate brain-based models, guided by the overall architecture of the brain, and by its developmental learning stages, can help attain high-level cognitive processing capabilities. Show basic language understanding and reasoning abilities for direct human-machine communication, at the level of a pre-school child, mimicking solutions used by the human brain.Show basic language understanding and reasoning abilities for direct human-machine communication, at the level of a pre-school child, mimicking solutions used by the human brain. Develop an attention control systems for focusing in sensory surveillance tasks, and for image searching.Develop an attention control systems for focusing in sensory surveillance tasks, and for image searching. Development of control structures for autonomous machines.Development of control structures for autonomous machines. Create its own goals in an autonomous fashion.Create its own goals in an autonomous fashion. Founded on neuro-scientific understanding of attention and the sensory and motor systems it controls, development in children, simplified modeling, computer power.Founded on neuro-scientific understanding of attention and the sensory and motor systems it controls, development in children, simplified modeling, computer power.
  • Slide 4
  • Sketch of the ABACCUS system Rough sketch of the ABACCUS system, based on simplified spiking neurons. Computational Platform, Simulation Environment and Integration Neuroscience and Development Vision Memory System Drive and Intrinsic reward system Atomization system Reasoning System Feedback Attention Control system Motor Control SpeechTactile Learning of PFC goals Working Memory Value Maps Action/Object reward system
  • Slide 5
  • Primary objective 1 To develop linguistic powers of ABACCUS system. To develop linguistic powers of ABACCUS system. Use training of single words by associating their representations to internal representations of objects and actions. Use training of single words by associating their representations to internal representations of objects and actions. Use pair-wise associations to learn word pairs (like kick ball), extend syntactically and functionally the use of function words. Use pair-wise associations to learn word pairs (like kick ball), extend syntactically and functionally the use of function words. Working memory modules, with associated phonological coding, will be created and fused in the language component, both for speech understanding and generation. Working memory modules, with associated phonological coding, will be created and fused in the language component, both for speech understanding and generation. Extension for abstract concepts by tagging the associated words to clusters of concrete object/action representations. Extension for abstract concepts by tagging the associated words to clusters of concrete object/action representations.
  • Slide 6
  • Primary objective 2 To create a high-level cognitive system, able to solve problems requiring reasoning, thinking, imagination and creativity. To create a high-level cognitive system, able to solve problems requiring reasoning, thinking, imagination and creativity. Based on the basic control concept of a forward model, acting as a predictor and working under attention control. Based on the basic control concept of a forward model, acting as a predictor and working under attention control. Forward models include various semantic and goal networks. Forward models include various semantic and goal networks. Sequences of activations of representations will be learnt and thereby used to achieve goals. Sequences of activations of representations will be learnt and thereby used to achieve goals. Various of these forward models will be present and branch into each other during the running process by means of lateral connections. Various of these forward models will be present and branch into each other during the running process by means of lateral connections. New routes will occur allowing complex goals to be achieved, or even new, previously unrecognized goals, to be arrived at (required for creativity). New routes will occur allowing complex goals to be achieved, or even new, previously unrecognized goals, to be arrived at (required for creativity).
  • Slide 7
  • Example of action internal models Rough sketch of the ACTION subnetwork. Sensory information enters the supplementary motor area (SMA) (1) cortico-thalamo-cortical (the short loop); (2) cortico-striatal-GPi-thalamo- cortical (the long loop); (3) cortico-(STN GPe)-GPi- thalamo-cortical (first indirect loop); (4) cortico-striatal-(STN GPe)-GPi- thalamo-cortical (the second indirect loop).
  • Slide 8
  • Primary objective 3 Extract a simplified architecture for the attention control system. Extract a simplified architecture for the attention control system. Should involve both sensory and motor control, especially joint sensory-motor control, systems whose creation is guided by neuroscientific knowledge about the brain. Should involve both sensory and motor control, especially joint sensory-motor control, systems whose creation is guided by neuroscientific knowledge about the brain. Approach based on infant development to train ABACCUS incrementally on the computer platform. Approach based on infant development to train ABACCUS incrementally on the computer platform. Use neuroscientific data to guide the architecture of a large-scale neural simulation of the relevant components of the human brain. Use neuroscientific data to guide the architecture of a large-scale neural simulation of the relevant components of the human brain. Use feed-forward/feedback training simulations based on the simplified brain architecture following developmental processes, using the sensor and response signals of the robotic embodiment. Use feed-forward/feedback training simulations based on the simplified brain architecture following developmental processes, using the sensor and response signals of the robotic embodiment.
  • Slide 9
  • Primary objective 4 Developing the ability to learn novel objects, both as stimuli and as associated reward values. Developing the ability to learn novel objects, both as stimuli and as associated reward values. Use reward/penalty feedback training with attention control, with associated value maps constructed to learn to encode the values of stimuli and responses to them in the environment. Use reward/penalty feedback training with attention control, with associated value maps constructed to learn to encode the values of stimuli and responses to them in the environment. Temporal sequence or schemata (as object/action sequences as well as the associated rewards involved) will be constructed to function as predictors and so support reasoning, along with automatic response learning. Temporal sequence or schemata (as object/action sequences as well as the associated rewards involved) will be constructed to function as predictors and so support reasoning, along with automatic response learning. Neural codes of visual, auditory and tactile concepts will be learnt in a feedforward manner, without attention, as will codes for motor responses controlling the embodied robot. Neural codes of visual, auditory and tactile concepts will be learnt in a feedforward manner, without attention, as will codes for motor re

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