:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Kortus, Tobias, Keidel, Ralf, Gauger, Nicolas R., Kieseler, Jan
Format:	Preprint
Published:	2025
Subjects:	Computational Physics Artificial Intelligence Machine Learning
Online Access:	https://arxiv.org/abs/2501.05113
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Exploring End-to-end Differentiable Neural Charged Particle Tracking -- A Loss Landscape Perspective
by: Kortus, Tobias, et al.
Published: (2024)

Supplementary Data for "Constrained collaborative optimization of charged particle tracking with multi-agent reinforcement learning"
by: Kortus, Tobias, et al.
Published: (2026)

Multi-Agent Deep Reinforcement Learning Under Constrained Communications
by: Shaik, Shahil, et al.
Published: (2026)

Supervised Metric Regularization Through Alternating Optimization for Multi-Regime Physics-Informed Neural Networks
by: Spotorno, Enzo Nicolas, et al.
Published: (2026)

Empirical Stability Analysis of Kolmogorov-Arnold Networks in Hard-Constrained Recurrent Physics-Informed Discovery
by: Spotorno, Enzo Nicolas, et al.
Published: (2026)

A Study on Optimization Techniques for Variational Quantum Circuits in Reinforcement Learning
by: Kölle, Michael, et al.
Published: (2024)

Integrating Policy Summaries with Reward Decomposition for Explaining Reinforcement Learning Agents
by: Septon, Yael, et al.
Published: (2022)

HIPO: Instruction Hierarchy via Constrained Reinforcement Learning
by: Chen, Keru, et al.
Published: (2026)

Compositional Shielding and Reinforcement Learning for Multi-Agent Systems
by: Brorholt, Asger Horn, et al.
Published: (2024)

Scalable Constrained Multi-Agent Reinforcement Learning via State Augmentation and Consensus for Separable Dynamics
by: Amaya-Corredor, Santiago, et al.
Published: (2026)

Large Language Models for Human-Machine Collaborative Particle Accelerator Tuning through Natural Language
by: Kaiser, Jan, et al.
Published: (2024)

$K$-Level Policy Gradients for Multi-Agent Reinforcement Learning
by: Reddi, Aryaman, et al.
Published: (2025)

NePPO: Near-Potential Policy Optimization for General-Sum Multi-Agent Reinforcement Learning
by: Kalanther, Addison, et al.
Published: (2026)

Incentivizing Safer Actions in Policy Optimization for Constrained Reinforcement Learning
by: Hazra, Somnath, et al.
Published: (2025)

Emergent Cooperation in Quantum Multi-Agent Reinforcement Learning Using Communication
by: Kölle, Michael, et al.
Published: (2026)

Unveiling Multi-regime Patterns in SciML: Distinct Failure Modes and Regime-specific Optimization
by: Wang, Yuxin, et al.
Published: (2026)

Multi-Modal Multi-Agent Reinforcement Learning for Radiology Report Generation
by: Baba, Kaito, et al.
Published: (2026)

RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning
by: Wang, Zihan, et al.
Published: (2025)

Offline Multi-Agent Reinforcement Learning via In-Sample Sequential Policy Optimization
by: Liu, Zongkai, et al.
Published: (2024)

Comparative Analysis of Multi-Agent Reinforcement Learning Policies for Crop Planning Decision Support
by: Mahajan, Anubha, et al.
Published: (2024)

An Offline Adaptation Framework for Constrained Multi-Objective Reinforcement Learning
by: Lin, Qian, et al.
Published: (2024)

Multi-Scenario Combination Based on Multi-Agent Reinforcement Learning to Optimize the Advertising Recommendation System
by: Zhao, Yang, et al.
Published: (2024)

Reinforce LLM Reasoning through Multi-Agent Reflection
by: Yuan, Yurun, et al.
Published: (2025)

AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning
by: Xi, Zhiheng, et al.
Published: (2025)

Hyperproperty-Constrained Secure Reinforcement Learning
by: Bonnah, Ernest, et al.
Published: (2025)

MARS: Co-evolving Dual-System Deep Research via Multi-Agent Reinforcement Learning
by: Chen, Guoxin, et al.
Published: (2025)

SPIRAL: Self-Play on Zero-Sum Games Incentivizes Reasoning via Multi-Agent Multi-Turn Reinforcement Learning
by: Liu, Bo, et al.
Published: (2025)

ML-Agent: Reinforcing LLM Agents for Autonomous Machine Learning Engineering
by: Liu, Zexi, et al.
Published: (2025)

ReMA: Learning to Meta-think for LLMs with Multi-Agent Reinforcement Learning
by: Wan, Ziyu, et al.
Published: (2025)

Safe and Balanced: A Framework for Constrained Multi-Objective Reinforcement Learning
by: Gu, Shangding, et al.
Published: (2024)

PDRL: Multi-Agent based Reinforcement Learning for Predictive Monitoring
by: Shaik, Thanveer, et al.
Published: (2023)

Training Language Models for Social Deduction with Multi-Agent Reinforcement Learning
by: Sarkar, Bidipta, et al.
Published: (2025)

Cheetah: Bridging the Gap Between Machine Learning and Particle Accelerator Physics with High-Speed, Differentiable Simulations
by: Kaiser, Jan, et al.
Published: (2024)

Collaborative Multi-Agent Reinforcement Learning for Automated Feature Transformation with Graph-Driven Path Optimization
by: Huang, Xiaohan, et al.
Published: (2025)

Decentralizing Multi-Agent Reinforcement Learning with Temporal Causal Information
by: Corazza, Jan, et al.
Published: (2025)

Optimizing Mission Planning for Multi-Debris Rendezvous Using Reinforcement Learning with Refueling and Adaptive Collision Avoidance
by: Bandyopadhyay, Agni, et al.
Published: (2026)

PMAT: Optimizing Action Generation Order in Multi-Agent Reinforcement Learning
by: Hu, Kun, et al.
Published: (2025)

Multi-Agent Reinforcement Learning for Resources Allocation Optimization: A Survey
by: Hady, Mohamad A., et al.
Published: (2025)

Continual Learning as Computationally Constrained Reinforcement Learning
by: Kumar, Saurabh, et al.
Published: (2023)

State-Constrained Offline Reinforcement Learning
by: Hepburn, Charles A., et al.
Published: (2024)