Adaptive risk-aware reinforcement learning framework for time-constrained navigation tasks. This MSc thesis studies how an RL agent can adapt its risk attitude when mission time changes, using a hierarchical controller that switches from a risk-aware CVaR-constrained policy to a risk-seeking policy when time pressure makes switching benificial.

Official code for "RiskZero: Plan More to Risk Less with a Learned Model"

A Reinforcement Learning MVP (Minimum Viable Product) for Condition-Based Maintenance (CBM) using industrial equipment temperature sensor data. This project implements a sophisticated QR-DQN (Quantile Regression Deep Q-Network) agent to learn optimal maintenance policies balancing risk mitigation and cost minimization.