This research presents a new framework for adaptive stress testing (AST) of autonomous vehicles (AVs). The study emphasizes the importance of ensuring the safety of AVs for their widespread adoption…
Continue readingThis paper introduces the Distributional Preference Reward Model (DPRM) to align large language models with a diverse set of human preferences. The researchers used a beta distribution to characterize preferences,…
Continue readingThe study introduces MAIDCRL (Multi-Agent Dense-CNN Reinforcement Learning), a reinforcement learning algorithm that incorporates convolutional layers into the deep model architecture for better multi-agent control in StarCraft Multi-Agent Challenge scenarios….
Continue readingThe study presents a novel approach to tackle the issues of stability and safety in robotic manipulators. The researchers propose an obstacle-free deep reinforcement learning (DRL) trajectory planner integrated with…
Continue readingThis academic paper focuses on the control of mobile robotic systems, specifically scaled robotic cars. The authors propose a two-stage least-square approach for parameter identification of the longitudinal and lateral…
Continue readingThe article presents a research on the use of deep reinforcement learning (DRL) for the control and positioning of scaled robotic vehicles. The authors propose a federated extended Kalman filter…
Continue readingThis paper presents a new approach to autonomous navigation using deep reinforcement learning (DRL). It addresses the issues of limited explainability and suboptimal performance in DRL by introducing three auxiliary…
Continue readingThe paper presents a two-step method for dynamic obstacle avoidance (DOA) in autonomous vehicles, crucial for any vehicle operating in sea, air, or land. The proposed architecture combines supervised and…
Continue readingThe paper discusses a novel Deep Reinforcement Learning (DRL) algorithm for designing optimal control policies for robots in unknown environments. The algorithm uses a mission-driven exploration strategy to prioritize exploration…
Continue readingThis paper proposes a new approach to optimize the coordination of drone swarms in Smart Cities. It combines distributed optimization and deep reinforcement learning (DRL) to improve navigation, sensing, and…
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