ADR Awareness Centre

This lecture will cover the basic concepts of Machine Learning to alleviate inconsistencies towards concept and notation accuracy. Supervised, self-supervised, unsupervised, semi-supervised learning. Multi-task Machine Learning.

This lecture overviews Agent Systems that has many applications in multi-party behavior modeling.

This lecture overviews Natural Selection simulation that has many applications in ecology and sociology studies.

This lecture overviews Robot and Drone Swarms that has many applications in autonomous systems: cars/drones.

This lecture overviews Self-Awareness that has many applications in in Autonomous Systems and robotics. It covers the following topics in detail: Self-awareness definition, Self-aware systems, Cognitive architecture.

When deployed, machine-learning (ML) adoption depends on its ability to actually deliver the expected service safely, and to meet user expectations in terms of quality and continuity of service.