Computational Vision & Robotics LaboratoryFORTH, Institute of Computer Science Towards Global Brain Models Stathis Kasderidis FORTH, ICS, Computer Vision.

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Computational Vision & Robotics LaboratoryFORTH, Institute of Computer Science Towards Global Brain Models Stathis Kasderidis FORTH, ICS, Computer Vision & Robotics Laboratory

Computational Vision & Robotics Laboratory FORTH, Institute of Computer Science 2 Methodological Observations A. Models tend to be increasingly accurate for low –level phenomena. B. Middle level modelling (3 or more) modules interacting not in focus! C. We need more experience with interactions in the middle level

Computational Vision & Robotics Laboratory FORTH, Institute of Computer Science 3 GNOSYS’ View

Computational Vision & Robotics Laboratory FORTH, Institute of Computer Science 4 Ventral pathway V1 V2 V4 TEO TE LGN Input Dorsal pathway V1 V5 LIP LGN Input Learning Hard-wired Currently Hard-wired Objects Oriented bars Movement Spatial position, colour, motion colour

Computational Vision & Robotics Laboratory FORTH, Institute of Computer Science 5 Goal Representation

Computational Vision & Robotics Laboratory FORTH, Institute of Computer Science 6 Goal Tree

Computational Vision & Robotics Laboratory FORTH, Institute of Computer Science 7 Implementation Details

Computational Vision & Robotics Laboratory FORTH, Institute of Computer Science 8 Attentional Agent Partition of Action Space:

Computational Vision & Robotics Laboratory FORTH, Institute of Computer Science 9 Questions 1. How do we arrive at concept representations incrementally 2. How do we retrieve salient concept features depending on context 3. How do we select the balance among processing and learning modes during operation

Computational Vision & Robotics Laboratory FORTH, Institute of Computer Science 10 Questions-2 4. How do we get concept salient features to represented as visual imagery 5. How do we achieve scenario blends 6. How concepts can be composed on the fly to facilitate imagination

Computational Vision & Robotics Laboratory FORTH, Institute of Computer Science 11 Questions-3 7. How do we achieve retrieval of the same semantic object in spite of different syntactical forms (conjunctive, disjunctive, negation, etc) 8. Analogical thinking… Many more…

Computational Vision & Robotics Laboratory FORTH, Institute of Computer Science 12 Conclusions Still we lack detailed understanding of the cognitive level module interactions! Thank you!