4 papers
HyPOLE: Hyperproperty-Guided Multi-Agent Reinforcement Learning under Partial Observation
Arshia Rafieioskouei, Tzu-Han Hsu, Matthew Lucas +1
Formal specification is a powerful tool to guide the learning process and provides significant advantages over reward shaping: (1) mathematical rigor; (2) expressiveness to specify…
Efficient Discovery of Actual Causality in Stochastic Systems
Arshia Rafieioskouei, Kenneth Rogale, Borzoo Bonakdarpour
Identifying the actual cause of events in engineered systems is a fundamental challenge in system analysis. Finding such causes becomes more challenging in the presence of noise an…
HypRL: Reinforcement Learning of Control Policies for Hyperproperties
Tzu-Han Hsu, Arshia Rafieioskouei, Borzoo Bonakdarpour
Reward shaping in multi-agent reinforcement learning (MARL) for complex tasks remains a significant challenge. Existing approaches often fail to find optimal solutions or cannot ef…
Efficient Discovery of Actual Causality using Abstraction-Refinement
Arshia Rafieioskouei, Borzoo Bonakdarpour
Causality is the relationship where one event contributes to the production of another, with the cause being partly responsible for the effect and the effect partly dependent on th…