Queue-Based Resampling (QBR, ICANN 2018)
This is a pip package implementing Reinforcement Learning algorithms in non-stationary environments supported by the OpenAI Gym toolkit.
Continual Reinforcement Learning in 3D Non-stationary Environments
Code associated with the NeurIPS19 paper "Weighted Linear Bandits in Non-Stationary Environments"
Repo for course CSC2558: "Intelligent Adaptive Interventions" project in nonstationary contextual bandits.
Matlab laboratories for the course "Online Learning and Monitoring" at Politecnico di Milano
Work for CDC2020
The implementation of the Diversity Pool algorithm, proposed in the paper "Diversity-Based Pool of Models for Dealing with Recurring Concepts" and presented at IJCNN '18
Experiments for paper "Online Learning with Costly Features in Non-stationary Environments"
R package to apply the transformed-stationary extreme value analysis
Mitigating the Stability-Plasticity Dilemma in Adaptive Train Scheduling with Curriculum-Driven Continual DQN Expansion
Code for the manuscript 'Hierarchy of prediction errors shapes the learning of context-dependent sensory representations'
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