2 citations · 5 across the 37 of their papers we have counts for
5 papers · 1 filter
Cross-fitted Proximal Learning for Model-Based Reinforcement Learning
Nishanth Venkatesh, Andreas A. Malikopoulos
Model-based reinforcement learning is attractive for sequential decision-making because it explicitly estimates reward and transition models and then supports planning through simu…
Model-Based Reinforcement Learning Under Confounding
Nishanth Venkatesh, Andreas A. Malikopoulos
We investigate model-based reinforcement learning in contextual Markov decision processes (C-MDPs) in which the context is unobserved and induces confounding in the offline dataset…
A Communication-Efficient Decentralized Actor-Critic Algorithm
Xiaoxing Ren, Nicola Bastianello, Thomas Parisini +1
In this paper, we study the problem of reinforcement learning in multi-agent systems where communication among agents is limited. We develop a decentralized actor-critic learning f…
AI Recommendation Systems for Lane-Changing Using Adherence-Aware Reinforcement Learning
Weihao Sun, Heeseung Bang, Andreas A. Malikopoulos
In this paper, we present an adherence-aware reinforcement learning (RL) approach aimed at seeking optimal lane-changing recommendations within a semi-autonomous driving environmen…
A Q-learning Approach for Adherence-Aware Recommendations
Ioannis Faros, Aditya Dave, Andreas A. Malikopoulos
In many real-world scenarios involving high-stakes and safety implications, a human decision-maker (HDM) may receive recommendations from an artificial intelligence while holding t…