76 citations · 99 across the 10 of their papers we have counts for
10 papers
CODE-SHARP: Continuous Open-ended Discovery and Evolution of Skills as Hierarchical Reward Programs
Richard Bornemann, Pierluigi Vito Amadori, Antoine Cully
A core quality of general intelligence is the ability to open-endedly expand and evolve its set of mastered skills autonomously. While recent Foundation Model (FM) driven approache…
Learning Representations in Video Game Agents with Supervised Contrastive Imitation Learning
Carlos Celemin, Joseph Brennan, Pierluigi Vito Amadori +1
This paper introduces a novel application of Supervised Contrastive Learning (SupCon) to Imitation Learning (IL), with a focus on learning more effective state representations for…
Robust Imitation Learning for Automated Game Testing
Pierluigi Vito Amadori, Timothy Bradley, Ryan Spick +1
Game development is a long process that involves many stages before a product is ready for the market. Human play testing is among the most time consuming, as testers are required…
Behavioural Cloning in VizDoom
Ryan Spick, Timothy Bradley, Ayush Raina +2
This paper describes methods for training autonomous agents to play the game "Doom 2" through Imitation Learning (IL) using only pixel data as input. We also explore how Reinforcem…
Hearables: Ear EEG Based Driver Fatigue Detection
Metin C. Yarici, Pierluigi Amadori, Harry Davies +4
Ear EEG based driver fatigue monitoring systems have the potential to provide a seamless, efficient, and feasibly deployable alternative to existing scalp EEG based systems, which…
Hearables: Feasibility of Recording Cardiac Rhythms from Single Ear Locations
Metin Yarici, Wilhelm Von Rosenberg, Ghena Hammour +5
Wearable technologies are envisaged to provide critical support to future healthcare systems. Hearables - devices worn in the ear - are of particular interest due to their ability…
Support-weighted Adversarial Imitation Learning
Ruohan Wang, Carlo Ciliberto, Pierluigi Amadori +1
Adversarial Imitation Learning (AIL) is a broad family of imitation learning methods designed to mimic expert behaviors from demonstrations. While AIL has shown state-of-the-art pe…
Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation
Ruohan Wang, Carlo Ciliberto, Pierluigi Amadori +1
We consider the problem of imitation learning from a finite set of expert trajectories, without access to reinforcement signals. The classical approach of extracting the expert's r…
Real-Time Workload Classification during Driving using HyperNetworks
Ruohan Wang, Pierluigi V. Amadori, Yiannis Demiris
Classifying human cognitive states from behavioral and physiological signals is a challenging problem with important applications in robotics. The problem is challenging due to the…
An Efficient Manifold Algorithm for Constructive Interference based Constant Envelope Precoding
Fan Liu, Christos Masouros, Pierluigi Vito Amadori +1
In this letter, we propose a novel manifold-based algorithm to solve the constant envelope (CE) precoding problem with interference exploitation. For a given power budget, we desig…