A Unified View on Solving Objective Mismatch in Model-Based Reinforcement Learning
Model-based Reinforcement Learning (MBRL) aims to make agents more sample-efficient,
adaptive, and explainable by learning an explicit model of the environment. While the …
adaptive, and explainable by learning an explicit model of the environment. While the …
Value of Information and Reward Specification in Active Inference and POMDPs
R Wei - arXiv preprint arXiv:2408.06542, 2024 - arxiv.org
Expected free energy (EFE) is a central quantity in active inference which has recently
gained popularity due to its intuitive decomposition of the expected value of control into a …
gained popularity due to its intuitive decomposition of the expected value of control into a …
Bi-Level Control of Weaving Sections in Mixed Traffic Environments with Connected and Automated Vehicles
Connected and automated vehicles (CAVs) can be beneficial for improving the operation of
highway bottlenecks such as weaving sections. This paper proposes a bi-level control …
highway bottlenecks such as weaving sections. This paper proposes a bi-level control …
Probabilistic Modeling of False Beliefs and Team Coordination
PR da Silva Soares - 2024 - search.proquest.com
We use the probabilistic graphical model (PGM) framework to explore human interaction
dynamics in collaborative settings, focusing on false beliefs and team coordination. In …
dynamics in collaborative settings, focusing on false beliefs and team coordination. In …