Why Robots and Evolutionary Robotics – Short History of AI – Embodied Cognition. The tools of the Trade: Artificial Neural Network – Evolutionary Algorithms History: The First Years of Evolutionary Robotics

Minimal Cognition: Continuous Time Recurrent Neural Networks – Minimal Cognition – Active Categorical Perception. Locomotion: Legged Locomotion – Bipedal Locomotion. Challenges: Modularity – Genotype-to-Phenotype Map – NEAT/HyperNEAT Crossing the Reality Gap: Radical Envelope-of-Noise Hypothesis – GOLEM Project – Resilient Machines – Transferability. Scalability/Crowdsourcing: DotBot Project – Twitch Play Robotics

Collective Robotics: Swarm Robotics – Evolution of Communication. Evolving Bodies and Brains: First Attempts (Karl Sim’s Works) – LSystem Robots – Why Evolve Bodies – Adaptive Robots – Soft Robots

Pre-Requisite(s): Python/C++, Basics of Computer Science
Course Type: Lab

Course Objectives

• This course aims to provide theories, methods, and technologies for designing robots and artificial systems inspired by evolution, development, and learning.
• The course also aims to show how robotic models can help to understand biological systems.

Course Outcomes
CO1: Understand the essential concepts of simulated evolution, development and learning in the context of robotic design.
CO2: Apply Evolutionary Computation and learning for design and development of artificial adaptive systems.
CO3: Apply new tools for evolving robot body and brains
CO4: Evaluate the evolution and learning techniques for design of robots

CO-PO Mapping

Evaluation Pattern: 70/30

Note: Continuous assessments can include quizzes, tutorials, lab assessments, case study and project reviews. Midterm and End semester exams can be a theory exam or lab integrated exam for two hours

1. Stefano Nolfi (2021). Behavioral and Cognitive Robotics: An Adaptive Perspective. Open Access Book.
2. Patricia A. Vargas, Ezequiel A. Di Paolo, Inman Harvey and Phil Husbands (Eds.) (2014). The Horizons of Evolutionary Robotics. MIT Press.
3. Dario Floreano and Claudio Mattiussi (2008). Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies. The MIT Press.
4. Rolf Pfeifer and Josh C. Bongard (2006). How the Body Shapes the Way We Think: A New View of Intelligence (Bradford Books). The MIT Press.
5. Additional readings from current research literature.