reinforcement learning

Multi-Agent Reinforcement Learning for Stochastic OSAT Dispatching: A Matched Architecture Benchmark

Physics-prior-driven distributed deep reinforcement learning for multi-UAV path planning

A physics-prior-driven decentralized deep reinforcement learning (DRL) framework Functioning as a scalable distributed computing paradigm via decentralized training with decentralized execution (DTDE), the framework mitigates the curse of dimensionality.

Review of key technologies for robot embodied intelligence oriented toward flexible manufacturing

The review finds that multimodal fusion and semantic SLAM are overcoming perception bottlenecks, that deep learning and force/position hybrid control are balancing flexible adaptability with high-precision operation, and that deep reinforcement learning and large models are advancing intelligent process planning.

CoSIPR: Shared Service Orchestration with Dynamic Interest Coalitions in Edge Computing

Experiments show that CoSIPR improves service-category matching, request satisfaction, and the average number of accepted requests per instance, and reduces aggregate state-transfer cost and limits hotspot exposure while maintaining a controlled trade-off between end-to-end delay and state-transfer cost.

Instilling Character Education Values through the Traditional Game of Selodor for Fourth-Grade Students at MI Al-Ijtihad Jontak

Traditional games remain underutilized in educational settings despite their potential to foster character development through experiential learning and social interaction. This study examines the implementation of the traditional selodor game in character education, identifies the character values manifested during pl...

Supplementary document for Reinforcement learning optimization of a ⁶Li magneto-optical trap: DDPG versus SAC - 8037132.pdf

8 pages and 7 sections

Behavior-based hybrid-action deep reinforcement learning for intelligent building energy management

A data-driven reinforcement learning framework for optimal balance control and stabilization of a rotary inverted pendulum

Adaptive SOH-Aware Frequency Regulation for Energy Storage Systems via Deep Reinforcement Learning

Reinforcement learning optimization of a ⁶Li magneto-optical trap: DDPG versus SAC

We report an experimental implementation of deep reinforcement learning (RL) for optimizing the loading stage of a ⁶Li magneto-optical trap (MOT) in a high-dimensional continuous control space. An off-policy actor-critic agent observes in-situ fluorescence images at 111 ms intervals and updates seven experimental param...

Energy-efficient FPGA acceleration of reinforcement learning algorithms using high-level synthesis

The results show that pipelined fixed-point FPGA architectures are a good solution to speed up the reinforcement learning process in resource-limited embedded systems.

Reinforcement-Learning-Based Energy Management for a Range-Extended Distributed-Drive Tracked Combine Harvester in Hilly Terrain

Farmland in the hilly and mountainous regions of southern China is characterized by complex terrain and highly variable operating loads. Conventional diesel-powered tracked harvesters are constrained by high crop losses, excessive impurity rates, frequent blockages, and low overall energy-use efficiency. Distributed el...