Three days at the Dagstuhl seminar on Explainable AI for Sequential Decision Making have just ended. Thanks to Abhinav Verma,…
Lessons Learnt
Evolutionary Algorithms in a Nutshell
Assisting Stéphane Doncieux with the practicals on Evolutionary Algorithms over the past few years, I had the chance to learn…
From Reinforcement Learning to Deep Reinforcement Learning
Reinforcement learning boasts a substantial history predating the recent surge in deep learning. Reinforcement learning is learning what to do—how…
ICRA 2023: Explainable Robotics Workshop
After being able to take part in a few in-person conferences at the beginning of my PhD, such as AAMAS…
PhD Done: Leveraging Other Experiences Made It Possible
The research I discuss in my thesis can be seen as a meta-reflection of my PhD journey. Leveraging other experiences…
Learning by Teaching: Sparse Notes on the Protégé Effect
“when we teach, we learn.” Seneca Besides working on my own research, the PhD gave me the chance to teach…
AAAI 22 – Explainable Agency in Artificial Intelligence Workshop
As last year, this year I co-organized the AAAI-22 Workshop on Explainable Agency in Artificial Intelligence. Despite the amount of time…
Explaining the Outputs of Transformers Models: A Working Example
Most of the information available worldwide is in text form, from legal documents to medical reports. A variety of deep…
ANIMATAS Symposium
The Symposium on Human-Machine Interaction: Perception, Social Learning, Personalised Adaptation in Educational Settings has just came to an end. Moderated…
Inverse Reinforcement Learning from a Gradient-based Learner
While searching for gradient based approaches in Inverse Reinforcement Learning, I came across the recent contribution of Ramponi et al.…
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