1. 9.4 Robust Best-arm Identification in Linear Bandits
   • Authors: Wei Wang, Sattar Vakili, Ilija Bogunovic
   • Reason: Presents a novel solution to a robust decision-making problem with practical relevance in adaptive systems such as diabetes care, indicating direct applications and potential high impact.
2. 9.1 Enhancing Multi-Agent Coordination through Common Operating Picture Integration
   • Authors: Peihong Yu, Bhoram Lee, Aswin Raghavan, Supun Samarasekara, Pratap Tokekar, James Zachary Hare
   • Reason: Accepted in OODWorkshop@CoRL23 indicating authority, and addresses a fundamental issue in MARL, a subset of reinforcement learning, showing significant results in established environments which is an indicator of influence.
3. 8.7 Real-Time Recurrent Reinforcement Learning
   • Authors: Julian Lemmel, Radu Grosu
   • Reason: Presents a novel reinforcement learning algorithm with a biologically plausible method for solving POMDPs with potential for significant practical applications, indicating a strong influence within the niche of bio-inspired RL algorithms.
4. 8.5 Zeroth-order Asynchronous Learning with Bounded Delays with a Use-case in Resource Allocation in Communication Networks
   • Authors: Pourya Behmandpoor, Marc Moonen, Panagiotis Patrinos
   • Reason: The paper tackles distributed optimization with potential applications in reinforcement learning, backed by convergence analyses and numerical experiments which suggest its potential influence in distributed RL applications.
5. 8.2 Toward Rapid, Optimal, and Feasible Power Dispatch through Generalized Neural Mapping
   • Authors: Meiyi Li, Javad Mohammadi
   • Reason: Addresses the feasibility of ML solutions in power systems, presenting a methodology to accelerate the optimization process which might influence the application of reinforcement learning in system control and power dispatch.