Topological Semiotic Knowledge Representation

This chapter describes cognitive models that organize implicit symbols into meaningful relational network structures. With an understanding of implicit symbols, there is evidence that informational processes on the cortical level can create and maintain multileveled hierarchically nested graphs and diagram – like structures. This topological model reflects hierarchically ordered knowledge of world structure and processes. Suggested models reflect systems, and they have structural relations embedded in the model. Ability to generate on fly new meaningful graphs and diagrams allows for modeling phenomena of intelligence like analogies, conceptual blending, and many others.

Topological Semiotics of Visual Information

This chapter explains how active vision and image understanding can be implemented with topological semiotic models, using cognitive architecture with perceptual mechanisms similar to human vision.

Driving Mechanisms and Patterns

This chapter explains role of positive and negative feedback mechanisms that are similar to emotions, and can drive processes to reach goals.

Cognitive Semiotics and the Game of Life

This chapter briefly describes overall architectural requirements to the autonomous systems, and provides details on how implicit perceptual symbols emerge in the brain, some evidence from neuroscience, and mathematical methods that can generate implicit symbols from perceptual information.

Practical Implementation Considerations

This chapter briefly describes APIs that could be used today for prototyping or implementing proposed architecture and methods.