85 citations · 354 across the 71 of their papers we have counts for
86 papers
Regret-Free Reinforcement Learning for LTL Specifications
Rupak Majumdar, Mahmoud Salamati, Sadegh Soudjani
Learning to control an unknown dynamical system with respect to high-level temporal specifications is an important problem in control theory. We present the first regret-free onlin…
Generative AI for Programming Education: Benchmarking ChatGPT, GPT-4, and Human Tutors
Tung Phung, Victor-Alexandru Pădurean, José Cambronero +5
Generative AI and large language models hold great promise in enhancing computing education by powering next-generation educational technologies for introductory programming. Recen…
Markov Decision Processes with Time-Varying Geometric Discounting
Jiarui Gan, Annika Hennes, Rupak Majumdar +2
Canonical models of Markov decision processes (MDPs) usually consider geometric discounting based on a constant discount factor. While this standard modeling approach has led to ma…
Neural Abstraction-Based Controller Synthesis and Deployment
Rupak Majumdar, Mahmoud Salamati, Sadegh Soudjani
Abstraction-based techniques are an attractive approach for synthesizing correct-by-construction controllers to satisfy high-level temporal requirements. A main bottleneck for succ…
Checking Refinement of Asynchronous Programs against Context-Free Specifications
Pascal Baumann, Moses Ganardi, Rupak Majumdar +2
In the language-theoretic approach to refinement verification, we check that the language of traces of an implementation all belong to the language of a specification. We consider…
Stochastic Principal-Agent Problems: Efficient Computation and Learning
Jiarui Gan, Rupak Majumdar, Debmalya Mandal +1
We introduce a stochastic principal-agent model. A principal and an agent interact in a stochastic environment, each privy to observations about the state not available to the othe…