When Does Information Sharing Improve Decentralized Discovery? Aggregation, Independent Rescue, and Equilibrium Selection

arXiv:2609.01814 · cs.AI, cs.GT · Submitted 2026-09-01 · Read on arXiv

cs.AI, cs.GT

Submitted: 2026-09-01

Updated: 2026-09-01

Code: https://github.com/yoheinakajima/distributed-discovery

Project page: https://yoheinakajima.github.io/distributed-discovery/publications/incentive-to-ignore.html

Terminology

• Accuracy — 34× in this paper · explained in 1 episode
• Aggregation — 21× in this paper · explained in 1 episode
• Benchmark — 7× in this paper · explained in 2 episodes
• Verification — 3× in this paper · explained in 2 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Provenance — 2× in this paper · explained in 4 episodes
• Multi-Agent System — 1× in this paper · explained in 6 episodes
• Nash Equilibrium — 1× in this paper · explained in 2 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems
• VSAL: A Vision Solver with Adaptive Layouts for Graph Property Detection