3 papers
cs.LO2026
Multi-Environment MDPs with Prior and Universal Semantics
Benjamin Bordais, Jean-François Raskin
Multiple-environment Markov decision processes (MEMDPs) equip an MDP with several probabilistic transition functions (one per possible environment) so that the state is observable…
cs.CC2025
Learning DFAs from Positive Examples Only via Word Counting
Benjamin Bordais, Daniel Neider
Learning finite automata from positive examples has recently gained attention as a powerful approach for understanding, explaining, analyzing, and verifying black-box systems. The…
cs.LO2025
A framework for computing upper bounds in passive learning settings
Benjamin Bordais, Daniel Neider
The task of inferring logical formulas from examples has garnered significant attention as a means to assist engineers in creating formal specifications used in the design, synthes…