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Defensive Sufficiency in a Stackelberg Model of AI Security
Oct 7, 2026Subhabrata Majumdar, Rajlakshmi ChavanCybersecurity Stackelberg Games
Indian Institute of Management Bangalore
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ECE Department, UC San Diego
CoNav-UAV: Cooperative Dual-Altitude Aerial Navigation via Stackelberg Learning
Aug 3, 2026Junru Song, Wenhao Zhang, Yang Yang +7UAV Navigation Stackelberg Games
1Shanghai Jiao Tong University · 2Intelligent Game and Decision Laboratory · 3Renmin University of China +1
Entropy-Regularized Reinforcement Learning for Linear-Quadratic Stackelberg Differential Games in Regime-Switching Diffusion Models
Jun 27, 2026Congde Hu, Danping Li, Lin Xu +1Stackelberg Games Maximum Entropy RL
School of Mathematics and Statistics, Anhui Normal University, Wuhu, Anhui 241002, China · School of Statistics, Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE, Faculty of Economics and Management, East China Normal University, Shanghai, China · School of Mathematics, Southeast University, Nanjing, Jiangsu 211189, China
A Stackelberg Framework for Resource-Aware LLM Agents: Learning, Repair, and Conditional Guarantees
Jun 22, 2026Baoxun WangStackelberg Games AI Agent Governance
Platform and Content Group, Tencent
Learning from Acceptance: Cumulative Regret in the Game of Coding
May 10, 2026Hanzaleh Akbari Nodehi, Parsa Moradi, Mohammad Ali Maddah-AliImperfect-Information Games Game Theory
University of Minnesota, Twin Cities, Minneapolis, MN, USA
Rethinking Priority Scheduling for Sequential Multi-Agent Decision Making in Stackelberg Games
May 8, 2026Xiangyu Liu, Liang Zhang, Bo Jin +1Sequential Decision Making Hierarchical RL
Dalian University of Technology
A Benchmark for Strategic Auditee Gaming Under Continuous Compliance Monitoring
May 7, 2026Florian A. D. Burnat, Brittany I. DavidsonAlgorithmic Auditing Stackelberg Games
University of Bath, Bath, England, UK.
Evolutionarily Stable Stackelberg Equilibrium
Mar 19, 2026Sam GanzfriedGame Theory Stackelberg Games
Ganzfried Research, Cornell University
LLM-Empowered Agentic MAC Protocols: A Dynamic Stackelberg Game Approach
Oct 13, 2025Renxuan Tan, Rongpeng Li, Fei Wang +4Agentic RL Stackelberg Games
College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China · Huawei Technologies Company Ltd., Shanghai 210026, China · Zhejiang Lab as well as Zhejiang University, Hangzhou 310027, China +1
Learning in Structured Stackelberg Games
Apr 11, 2025Maria-Florina Balcan, Kiriaki Fragkia, Keegan HarrisGame Theory Stackelberg Games
Carnegie Mellon University, Pittsburgh, USA · University of California, Berkeley, USA
Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents
Jun 5, 2023Nika Haghtalab, Chara Podimata, Kunhe YangImperfect-Information Games Game Theory
University of California, Berkeley · Massachusetts Institute of Technology

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Defensive Sufficiency in a Stackelberg Model of AI Security

Subhabrata Majumdar, Rajlakshmi Chavan

Indian Institute of Management Bangalore

Cybersecurity Stackelberg Games

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Feedback from automated testing, human red teaming, and incident response can strengthen an AI system's defenses when discovered failures lead to effective repairs. We study when this feedback process provides sufficient protection and when investing in it is economically worthwhile. We begin by showing that an attack surface composed of finite number of inputs is defended with probability 1 if every unresolved attack has a persistent chance of discovery, repairs are effective, and subsequent updates preserve earlier protection. We derive completion-time bounds and extend the analysis to growing attack surfaces, repairs that generalize across related attacks, and multiple discovery mechanisms. These results distinguish eventual protection against each fixed attack from complete protection at a single time. We then formulate a defender-led Stackelberg game in which the defender invests in proactive discovery and reactive repair, anticipating the attacker's choice of search effort. We characterize the least-cost allocation that deters attack and the equilibrium regimes in which the defender funds neither capability, one capability, or both. Numerical experiments illustrate these regimes and show how faster repair can reduce compromise duration without reducing compromise probability.unified theory of performance limits in generative language models.

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