7 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…
Lattice Aggregation in Distributed Verification under Crash and Byzantine Failures
Gilde Valeria RodrÃguez, Borzoo Bonakdarpour, Armando Castañeda +1
We introduce c-Lattice Aggregation, a fault-tolerant reconstruction problem for distributed verification under crash and Byzantine failures. In our setting, n asynchronous processe…
Tractable Hyperproperties for MDPs
Lina Gerlach, Tobias Winkler, Erika Ãbrahám +2
Probabilistic hyperproperties describe probabilistic relations between multiple sets of executions in a stochastic system. Prominent examples include information-theoretic characte…
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…
HyperQB: A Bounded Model Checker for Hyperproperties
Tzu-Han Hsu, Milad Rabizadeh, Kenneth Rogale +4
We introduce the tool HyperQB 2.0, the first highly efficient push-button bounded model checker (BMC) for hyperproperties. HyperQB takes as input a model in NuSMV or Verilog and a…