Major milestone achieved! Successfully defended PhD thesis on brain-inspired memory architectures for cognitive robotics.
Thesis Overview
“Towards a Brainlike Memory for Cognitive Robots”
The central premise of the thesis is that cognition is constructive manipulation of memory. Based on this principle, it proposes a novel brain-guided perspective on the design of cognitive architectures for cumulatively developing systems.
Key Contributions
Theoretical Framework
- Brain-inspired memory architectures for robots
- Constructive manipulation of memory as the foundation of cognition
- Principled framework for cumulative learning
Experimental Validation
The framework was validated through several experiments from animal and infant cognition reenacted on the iCub humanoid robot:
- Learning of actions and motor skills
- Affordance discovery and learning
- Cause-effect relationship understanding
- Multi-modal sensory integration
Cumulative Development
The thesis demonstrates how robots can achieve cumulative learning across multiple cognitive domains, building increasingly sophisticated behavioral repertoires over time.
Impact
This work establishes foundational principles for designing cognitive robots that can learn and develop in human-like ways, with memory systems that support both storage and creative recombination of experiences.
Feedback and discussions welcomed from the research community!