Evolving complete cognitive architectures: The role of neural - - PowerPoint PPT Presentation
Evolving complete cognitive architectures: The role of neural - - PowerPoint PPT Presentation
Evolving complete cognitive architectures: The role of neural competition and diffusive emotional control for learning and emergent cognitive capabilities Claudius Gros, Gregor Kaczor Institute for Theoretical Physics Goethe University
Assumption
A complete cognitive agent is not just a
complex input-output device, driven by the sensory input, but characterized by autonomously generated internal activities.
If so, how and when do these internal states
and activity patterns build up the correlation with information it receives via the sensory data input stream?
Assumption
We think, that correlations between internal and
external states are generated whenever the later are able to influence and modify the internal thought processes.
Cognitive System with autonomous dynamics
Dhan Layer Input Layer Backlinks
Dhan Layer Input Layer Backlinks
Dense Homogeneous Associative Network Model
Autonomous dynamics layer
Inhibitory background Excitatory links
- Dashed lines
- reservoir
- Continuous lines- activities
Autonomous internal activity and clique encoding
- Dashed lines
- reservoir
- Continuous lines- activities
Fully connected layers
Dhan Layer Input Layer Backlinks
Dense Homogeneous Associative Network Model
Dhan Layer Input Layer Backlinks Regular Stimuli 90% Noise Stimuli 10%
Dhan Layer Input Layer Backlinks Regular Stimuli 90% Noise Stimuli 10%
Dense Homogeneous Associative Network Model
Lerning between Layers
Dhan Layer Input Layer Backlinks
Dhan Layer Input Layer Backlinks Regular Stimuli 90% Noise Stimuli 10% Receptive Field
Receptive Field
Receptive Field
Model
ri= f w
post∑ [wij wij] f w pre j x j−z tanh ri bare
ri
bare
˙ x=1−xiririxi−riri ri
bare=∑ j=1 N
zij f z j g zx j ˙ i=
positive1−x ina−xi− negativeixi−x act
References
Gros, C., and Kaczor, G. 2008. Learning in cognitive systems with autonomous dynamics. Arxiv preprint arXiv:0804.1306 Gros, C. 2005. Self-sustained thought processes in a dense associative network. In Lecture notes in computer science, volume 3698, 366-379. Springer Gros, C. 2007. Neural Networks with transient state dynamics. New Journal of Physics 9:109 Gros, C. 2008. Complex and Adaptive Dynamical Systems. Springer. Gros, C. 2009. Emotions, diffusive emotional control and the motivational problem for autonomous cognitive systems. In Handbook of Research on Synthetic Emotions and Sociable Robotics: New Applications in Affective Computing and Artificial Intelligence.
- J. Vallverdu, D. Casacuberta (Eds.), IGI-Global. (in press)