High Volatility and Action Bias Distinguish LLMs from Humans in Group Coordination
High Volatility and Action Bias Distinguish LLMs from Humans in Group Coordination explores This research investigates the coordination capabilities of LLMs compared to humans in group tasks, identifying key behavioral differences to inform future agent development.. Commercial viability score: 3/10 in Agents.
Use This Via API or MCP
Use the canonical paper page as a proof artifact
This route is the stable paper-level surface for citations, viability, references, and downstream handoffs. Use it as the proof layer behind Signal Canvas, workspace creation, and launch-pack generation.
Owned Distribution
Subscribe to the weekly brief
Get the weekly shortlist of commercializable papers, benchmark movers, and proof receipts that matter for product execution.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $10K - $14K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisMore at Stake: How Payoff and Language Shape LLM Agent Strategies in Cooperation DilemmasViability: 2.0
- Builds On ThisMind the (DH) Gap! A Contrast in Risky Choices Between Reasoning and Conversational LLMsViability: 2.0
- Builds On ThisEvaluating LLM-Simulated Conversations in Modeling Inconsistent and Uncollaborative Behaviors in Human Social InteractionViability: 2.0
- Prior WorkProbing the Lack of Stable Internal Beliefs in LLMsViability: 3.0
- Prior WorkThis human study did not involve human subjects: Validating LLM simulations as behavioral evidence
Related Resources
- TransportAgents(glossary)
- AgentSpeak(glossary)
- Mixture-of-Agents(glossary)
- What is the future of AI agents according to Nothing's CEO?(question)
- How do LLM efficiency advancements impact the development of AI agents?(question)
- How does AgentXRay contribute to the explainability of AI agents in complex decision-making processes?(question)
- Agents – Use Cases(use_case)