“when we teach, we learn.” Seneca Besides working on my own research, the PhD gave me the chance to teach … More
Author: Silvia Tulli
Machine Learning and Robotics Researcher | Associate Professor
Identifying Sentiment-based Contradictions
Consulting other people’s opinions refines our own and helps us choose. Extracting useful information from those opinions, product reviews for … More
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 … More
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 … More
ANIMATAS Symposium
The Symposium on Human-Machine Interaction: Perception, Social Learning, Personalised Adaptation in Educational Settings has just came to an end. Moderated … More
gym-minigrid online manual control
To implement agents that can learn through social interaction as humans do, I decided to explore how humans instruct each … More
Counterfactually-Guided Policy Search
A compelling way to reduce the cost of real experience in reinforcement learning is to learn policies on data synthesised … More
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. … More
AAAI 21 – Explainable Agency in Artificial Intelligence Workshop
This year I had the great opportunity to co-organize the AAAI-21 Workshop on Explainable Agency in Artificial Intelligence together with … More
Learning Rewards from Linguistic Feedback
While discussing with my supervisor about how to move forward with our project, he suggested me to look at the … More
