Get Started
Home
Topics
Search
Library
Research questionHow should enterprise decision agents be evaluated when rankings change between fixed-opponent and shared-market settings?An agent may perform well against fixed opponents yet behave differently when other evaluated agents compete for shared resources. Evaluation design must therefore separate apparent model quality from effects caused by the surrounding competitive ecology.
AI
AI Agents
Business
Economics
Evaluation & Benchmarks
Multi-agent Systems
Latest papersRecent research connected to this question, newest first.ERPBench: Evaluating LLM Agents for Enterprise Decision-Making Across Competitive Market EcologiesThe source introduces a paired ERP simulation that compares fixed-opponent and shared-market evaluations over coupled enterprise decisions. Its evidence is limited to the tested service configuration, model families, tasks, and simulated market, rather than real-world enterprise performance.research paper · Sep 4, 2026
Related questions
How can agentic benchmarks be compared and reused across complex environments and bespoke agent integrations?When teams develop private coordination conventions, can role-matched agents be replaced without increasing communication or hurting task success?How can adaptive trading agents be stress-tested across alternative futures when returns hide state and execution failures?How can intelligent systems be compared under deployment constraints when representational economy, prediction, and resource use trade off?