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cs.AI2026
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…
cs.AI2025
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…