Hours:
8 hours (2 credits)

Room:

Meeting Room, Dept. of Information Engineering, Largo Lazzarino 1, Pisa, Sixth Floor

To register to the course, click here

Short Abstract:

Cognitive models play a central role in advancing autonomous and adaptive behavior in robotics by providing computational accounts of perception, memory, language, and decision-making. Rather than relying solely on task-specific control architectures, cognitively inspired systems aim to reproduce general mechanisms underlying human cognition, enabling learning, reasoning, and flexible interaction with the environment. This course introduces key principles of cognitive modeling in robotics, with particular emphasis on neural and symbolic–subsymbolic approaches. As a representative example, we consider the ANNABELL (Artificial Neural Network with Adaptive Behavior Exploited for Language Learning) model, which implements language acquisition and use through biologically inspired neural mechanisms and working-memory structures. ANNABELL illustrates how complex cognitive functions can emerge from the interaction of simple neural components, offering insights into scalable, brain-inspired architectures for cognitive robotics.  

Course Contents in brief:

1. Introduction to cognitive robotics and cognitive architectures
2. Biological and cognitive inspirations for robotic intelligence
3. Neural-based cognitive models and learning mechanisms
4. Symbolic and hybrid approaches to cognition in robots
5. Working memory, attention, and executive control
6. Language acquisition and processing in cognitive systems
7. The ANNABELL model: structure, neural mechanisms, and language learning
8. Applications, simulations, and relevance to autonomous robotic systems
9. Open research problems and future directions in cognitive robotics
10. Open Science approaches

Schedule:

Day 1 – March 24, 2026 – h. 11.00-13.00

Day 1 – March 24, 2026 – h. 14.00-18.00

Day 2 – March 27, 2026 – h 8.00-10.00: Final exam.