· Read in · 980 words · All posts in series · [dropcap]Sources[/dropcap] of inspiration is one thing we do not lack in machine learning. This is what, for me at least, makes machine learning research such a rewarding and exciting area to work in. We … Continue reading Cognitive Machine Learning: Prologue
· Read in · 2080 words · All posts in series · [dropcap]My[/dropcap] memory, like yours, exerts a powerful influence over my interaction with the world. It is reconstructive and evocative; I can easily form an image of hot December days in the South African summer, and remember my first time—it was … Continue reading Learning in Brains and Machines (4): Episodic and Interactive Memory
· Read in · 1796 words · All posts in series · [dropcap]There[/dropcap] is a dance—precisely choreographed and executed—that we perform throughout our lives. This is the dance formed by our movements. Our movements are our actions and the final outcome of our decision making processes. Single actions are … Continue reading Learning in Brains and Machines (3): Synergistic and Modular Action
· Read in · 1800 words · collected posts · We all make mistakes, and as is often said, only then can we learn. Our mistakes allow us to gain insight, and the ability to make better judgements and fewer mistakes in future. … Continue reading Learning in Brains and Machines (1): Temporal Differences
Marr's three levels of analysis [cite key="marr1982"] promotes the idea that complex systems such as the brain, a computer or human behaviour should be understood at different levels. Marr's framework proved to be an elegant and popular way of reasoning about complex systems, and in the context of machine learning and statistics, remains an intuitive framework that is often used when describing probabilistic models of cognition and perceptual systems.