Cover Image

Scaling Intelligent Agents in Combat Simulations for Wargaming

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Black, Scotty, Darken, Christian
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Scaling Artificial Intelligence for Digital Wargaming in Support of Decision-Making
by: Black, Scotty, et al.
Published: (2024)

A Hierarchical Hybrid AI Approach: Integrating Deep Reinforcement Learning and Scripted Agents in Combat Simulations
by: Black, Scotty, et al.
Published: (2025)

Mastering the Digital Art of War: Developing Intelligent Combat Simulation Agents for Wargaming Using Hierarchical Reinforcement Learning
by: Black, Scotty
Published: (2024)

Localized Observation Abstraction Using Piecewise Linear Spatial Decay for Reinforcement Learning in Combat Simulations
by: Black, Scotty, et al.
Published: (2024)

Intelligent Assistants for the Semiconductor Failure Analysis with LLM-Based Planning Agents
by: Dobrovsky, Aline, et al.
Published: (2025)

Explaining Strategic Decisions in Multi-Agent Reinforcement Learning for Aerial Combat Tactics
by: Selmonaj, Ardian, et al.
Published: (2025)

OPBench: A Graph Benchmark to Combat the Opioid Crisis
by: Ma, Tianyi, et al.
Published: (2026)

BuilderBench: The Building Blocks of Intelligent Agents
by: Ghugare, Raj, et al.
Published: (2025)

Distribution Fitting for Combating Mode Collapse in Generative Adversarial Networks
by: Gong, Yanxiang, et al.
Published: (2022)

Combating the Bucket Effect:Multi-Knowledge Alignment for Medication Recommendation
by: Li, Xiang, et al.
Published: (2025)

Combating Spurious Correlations in Graph Interpretability via Self-Reflection
by: Cai, Kecheng, et al.
Published: (2026)

SmartPlay: A Benchmark for LLMs as Intelligent Agents
by: Wu, Yue, et al.
Published: (2023)

Enhancing Aerial Combat Tactics through Hierarchical Multi-Agent Reinforcement Learning
by: Selmonaj, Ardian, et al.
Published: (2025)

Simulating Environments with Reasoning Models for Agent Training
by: Li, Yuetai, et al.
Published: (2025)

Dissecting Deep RL with High Update Ratios: Combatting Value Divergence
by: Hussing, Marcel, et al.
Published: (2024)

Combating Data Imbalances in Federated Semi-supervised Learning with Dual Regulators
by: Bai, Sikai, et al.
Published: (2023)

Deep Reinforcement Learning Agents are not even close to Human Intelligence
by: Delfosse, Quentin, et al.
Published: (2025)

On the Effects of Data Scale on UI Control Agents
by: Li, Wei, et al.
Published: (2024)

HingeRLC-GAN: Combating Mode Collapse with Hinge Loss and RLC Regularization
by: Goni, Osman, et al.
Published: (2025)

Understanding Agent Scaling in LLM-Based Multi-Agent Systems via Diversity
by: Yang, Yingxuan, et al.
Published: (2026)

Scaling Instructable Agents Across Many Simulated Worlds
by: SIMA Team, et al.
Published: (2024)

Scaling Laws for Pre-training Agents and World Models
by: Pearce, Tim, et al.
Published: (2024)

InSTA: Towards Internet-Scale Training For Agents
by: Trabucco, Brandon, et al.
Published: (2025)

Scaling Laws for Imitation Learning in Single-Agent Games
by: Tuyls, Jens, et al.
Published: (2023)

Energy-Efficient Domain-Specific Artificial Intelligence Models and Agents: Pathways and Paradigms
by: Chatterjee, Abhijit, et al.
Published: (2025)

Robust Federated Learning Over the Air: Combating Heavy-Tailed Noise with Median Anchored Clipping
by: Li, Jiaxing, et al.
Published: (2024)

Derived Fields Preserve Fine-Scale Detail in Budgeted Neural Simulators
by: Wang, Wenshuo, et al.
Published: (2026)

The PokeAgent Challenge: Competitive and Long-Context Learning at Scale
by: Karten, Seth, et al.
Published: (2026)

UI-Oceanus: Scaling GUI Agents with Synthetic Environmental Dynamics
by: Wu, Mengzhou, et al.
Published: (2026)

Reasoning as Gradient: Scaling MLE Agents Beyond Tree Search
by: Zhang, Yifei, et al.
Published: (2026)

Security Considerations for Artificial Intelligence Agents
by: Li, Ninghui, et al.
Published: (2026)

Symbolic Graph Intelligence: Hypervector Message Passing for Learning Graph-Level Patterns with Tsetlin Machines
by: Blakely, Christian D.
Published: (2025)

MLE-Smith: Scaling MLE Tasks with Automated Multi-Agent Pipeline
by: Qiang, Rushi, et al.
Published: (2025)

Thinking vs. Doing: Agents that Reason by Scaling Test-Time Interaction
by: Shen, Junhong, et al.
Published: (2025)

$\texttt{PatentAgent}$: Intelligent Agent for Automated Pharmaceutical Patent Analysis
by: Wang, Xin, et al.
Published: (2024)

MedAgentBench: A Realistic Virtual EHR Environment to Benchmark Medical LLM Agents
by: Jiang, Yixing, et al.
Published: (2025)

CUA-Gym: Scaling Verifiable Training Environments and Tasks for Computer-Use Agents
by: Wang, Bowen, et al.
Published: (2026)

OPT-BENCH: Evaluating LLM Agent on Large-Scale Search Spaces Optimization Problems
by: Li, Xiaozhe, et al.
Published: (2025)

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation
by: Dai, Weinan, et al.
Published: (2026)

ML-Driven Approaches to Combat Medicare Fraud: Advances in Class Imbalance Solutions, Feature Engineering, Adaptive Learning, and Business Impact
by: Farahmandazad, Dorsa, et al.
Published: (2025)