Theory
- Conducting fundamental research on the formalization of stage and stage transition dynamics in detail
- Mathematically discriminating the processes of learning and development, which are fundamentally different, but intrinsically correlated to a point where no clear discrimination has been achieved so far.
Measurement
Validation
- Using the previous formalization to the construction of self-organizing algorithms that follow the same laws of stage and stage transition
- Testing the validity of such processes in the domain of cognitive neuroscience to ensure that ethical and human-like machines are being addressed.
- Making sure that the exponential growth in complexity from one stage to another does not encompass a likewise exponential growth in computational resources.
Application
- Applying the rationale of the Model of Hierarchical Complexity to Behavioral and Social Sciences, Artificial Intelligence Neural Networks algorithms, and Robotics
Where we are
- Take a look at our developments!