LLMs as Strategic Actors: Behavioral Alignment, Risk Calibration, and Argumentation Framing in Geopolitical Simulations

A research study evaluated six state-of-the-art large language models in geopolitical crisis simulations, comparing their decision-making to human behavior. The study found that LLMs initially mirror human decisions but diverge over time, consistently exhibiting cooperative, stability-focused strategies with limited adversarial reasoning.

• →Six popular LLMs were tested in structured geopolitical simulations against human decision-making baselines.
• →Models initially approximated human decision patterns but showed divergent behavior over multiple simulation rounds.
• →All LLMs demonstrated strong normative-cooperative framing focused on stability and risk mitigation.
• →Models showed limited capacity for adversarial reasoning compared to human participants.
• →Research highlights behavioral differences between AI and human strategic decision-making in crisis scenarios.