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Published on: October 18, 2018
On the interactions between top-down anticipation and bottom-up regression
1Brain Science Institute, RIKEN Japan.
Frontiers in Neurorobotics
|October 30, 2008
Summary
This study explores anticipation and regression in cognitive behavior modeling. A neural network model highlights how the interplay and recovery between top-down anticipation and bottom-up regression are key to embodied cognition.
Area of Science:
- Cognitive Science
- Artificial Intelligence
- Robotics
Background:
- Cognitive behavior modeling often simplifies complex processes.
- Understanding anticipation and regression is crucial for realistic cognitive models.
- Embodied cognition emphasizes the role of physical interaction in cognition.
Purpose of the Study:
- To investigate the roles of anticipation and regression in cognitive behavior.
- To propose and evaluate a neural network model for these functions.
- To explore the link between these cognitive processes and embodied cognition.
Main Methods:
- Development of a novel neural network model.
- Implementation of the model in cognitive robotics experiments.
- Analysis of experimental results to understand cognitive phenomena.
Main Results:
- The neural network model successfully incorporated anticipation and regression.
- Experimental results demonstrated the importance of the interplay between these functions.
- The break-down and recovery between anticipation and regression were identified as key.
Conclusions:
- Anticipation and regression are fundamental to cognitive behavior.
- The proposed neural network model offers insights into embodied cognition.
- The dynamic interplay and recovery of these processes are central to embodied cognition.
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