reinforcement learning

Simulation data for "Internal-state criticality in Bayesian–inverse-Bayesian inference"

# Data archive — Internal-state criticality in Bayesian–inverse-Bayesian inference **Paper.** *Internal-state criticality in Bayesian–inverse-Bayesian inference*, K. Sasai and Y.-P. Gunji (Physical Review Research, submitted). **Source repository.** **DOI.** `10.5281/zenodo.20533918`. --- ## Contents This deposit conta...

Supplementary Information for the Paper "Physical Interaction Effects Reveal the Necessary

We conduct a systematic two-year experimental study across 22 contact-rich insertion tasks to determine whether the failure of learning-based robot control on tight-tolerance assembly reflects a fundamental structural limitation. Evaluating five levels of model knowledge across 693,000 real-hardware trials, we show tha...

QRL-FP: a quantum-inspired reinforcement learning framework for multi-objective system-on-chip floorplanning

Seq2Seq2Seq: lossless data compression via discrete latent transformers and reinforcement learning

Abstract Efficient lossless compression is essential for reducing storage and transmission requirements while preserving data exactly. Traditional dictionary-based and statistical compressors can be limited in their ability to exploit complex, long-range dependencies. In this paper, we propose a lossless compression fr...

STRATEGI GURU DALAM MENGELOLA KECEMASAN BERBAHASA SISWA KELAS VI PADA MAHARAH KALAM BAHASA ARAB

Arabic language learning as a foreign language is frequently hindered by foreign language anxiety, thereby affecting students' mastery of maharah kalam (speaking skills). However, if students continuously experience such anxiety, the objective of speaking instruction to enhance oral competence in Arabic will be difficu...

EOL-DQN: An intelligent cutting decision of potato seed tubers based on improved deep reinforcement learning

An explainable AI framework for crack width and crack spacing prediction with serviceability-oriented design optimization of reinforced and prestressed concrete members

Reliable prediction of cracking behavior is essential for the serviceability assessment of reinforced and prestressed concrete members, where crack development depends on interacting material, geometric, reinforcement, prestressing, and loading parameters. This study presents an explainable and uncertainty-aware artifi...

Trans-SAC: gamification design for sustained user engagement in residential demand response

Abstract Residential Demand Response (DR) is a critical mechanism for maintaining the supply-demand balance in modern smart grids. While gamification has recently emerged as a promising strategy to incentivize residential participation, existing programs suffer from severe long-term user fatigue. Once the initial "nove...

Data and code for "Humans and large language models rely on distinct strategies for adaptive decision-making under uncertainty"

human vs LLM in adaptive decision making, including four reinforcement learning tasks(one-armed, two-armed bandit tasks, reversal learning task and two-step task)

Moving target defense in 5G and beyond networks: A comprehensive survey and research directions

This paper presents a deployment-oriented survey of MTD for 5G, with special emphasis on learning-assisted designs that optimize what to mutate, when to mutate, and how to enforce mutation under slice-isolation, URLLC, and orchestration constraints.

ARISE: Reinforcement learning for dynamic critical-node intervention in rumor-epidemic co-evolution

A knowledge-guided hierarchical multi-agent deep reinforcement learning approach for crowd evacuation