reinforcement learning

A TSP solving model based on multiscale feature fusion and adaptive context awareness

Transformer-based deep reinforcement learning for the Traveling Salesman Problem (TSP) often struggles to capture spatial topology and avoid local optima. To address this, we propose a novel model featuring a Multi-Scale Grid Attention Encoder (MSGAE) to fuse local and global spatial features, alongside a bottleneck-en...

Adaptive Probabilistic Shielding by Learning MDPs for Safe Reinforcement Learning

Decision-Path Inverse Reconstruction: Observed Decision Outcomes as Structural Constraints on Latent Decision Paths

This working paper proposes Decision-Path Inverse Reconstruction (DPIR), an inverse analytical operation within the Atlas Insight Method (AIM). DPIR treats an observed decision outcome not only as the endpoint of a judgment process, but also as structural information that constrains the set of decision paths capable of...

Architectural Design Decisions for Monitoring Deployed Reinforcement Learning Systems

Hierarchical cooperative signal control for high-demand networks within the MFD framework: A deep reinforcement learning approach

PEMBERDAYAAN GURU DALAM PEMBUATAN MODUL PEMBELAJARAN BERBASIS DEEP LEARNING MELALUI KOLABORASI GURU PADA MGMP BAHASA INDONESIA SE-KOTA PALANGKA RAYA

The implementation of the Deep Learning approach within the Kurikulum Merdeka framework requires teachers to design instructional modules that facilitate meaningful, mindful, and joyful learning experiences. However, a preliminary needs assessment among teachers in the Indonesian Language Subject Teachers' Consultation...

ProcessLLM-R1: A hypergraph retrieval-augmented and reinforcement learning-driven assembly process planning for commercial aircraft

ElasticScale: Elastic Large Language Model Reinforcement Learning Training on Heterogeneous Mobile Edge Clusters

ElasticScale is presented, an elastic orchestration system that organizes heterogeneous accelerators into disaggregated rollout and trainer instances, via a HeterogeneousRayWorkerGroup abstraction that manages non-uniform hardware topologies and a multi-instance Federated Weight Averaging protocol that aggregates updat...

Identifiability of Ensemble Disagreement under One-Step Distillation

Model-based reinforcement learning gates imagined transitions by how much an ensemble disagrees, and diffusion world models are distilled into one-step students to make that imagination affordable. Whether distillation preserves the score the gate reads is rarely checked; we show that it need not. Matching the teacher'...

Gymnasium: A Standard Interface for Reinforcement Learning Environments

Gymnasium is an open-source library providing an API for reinforcement learning environments. Its main contribution is a central abstraction for wide interoperability between benchmark environments and training algorithms. Gymnasium comes with various built-in environments and utilities to simplify researchers' work al...

Database and code for punching shear of FRP-reinforced flat slabs: a leakage-aware benchmark

This dataset accompanies the manuscript "Do machine learning models outperform design codes for the punching shear strength of FRP-reinforced flat slabs? A leakage-aware benchmark with explainable analysis." It contains a database of 87 punching shear tests on interior slab–column connections reinforced with glass or c...

Manajemen Pemanfaatan Teknologi Digital dalam Mengoptimalkan Kualitas Pembelajaran Akidah Akhlak pada MAN 1 HSU

Digital transformation in Islamic education provides significant opportunities while simultaneously creating challenges in maintaining a balance between technological innovation and character value reinforcement. This study aims to analyze the management of digital technology utilization in optimizing the quality of Ak...