3 papers
cs.AI2026
Synthesizing POMDP Policies: Sampling Meets Model-checking via Learning
Debraj Chakraborty, Anirban Majumdar, Prince Mathew +2
Partially Observable Markov Decision Processes (POMDPs) are the standard framework for decision-making under uncertainty. While sampling-based methods scale well, they lack formal…
cs.FL2025
Learning Event-recording Automata Passively
Anirban Majumdar, Sayan Mukherjee, Jean-François Raskin
This paper presents a state-merging algorithm for learning timed languages definable by Event-Recording Automata (ERA) using positive and negative samples in the form of symbolic t…
cs.FL2024
Greybox Learning of Languages Recognizable by Event-Recording Automata
Anirban Majumdar, Sayan Mukherjee, Jean-François Raskin
In this paper, we revisit the active learning of timed languages recognizable by event-recording automata. Our framework employs a method known as greybox learning, which enables t…