Agent_Astronaut: Agent-Based Model Attributes for Lunar Mission Simulation

An Agent_Astronaut framework simulates social interactions and human factors for NASA's Artemis program. Monte Carlo simulations of tens of thousands of iterations explore trade-offs in productivity and psychological well-being for astronauts on the Lunar Gateway and South Pole Base. The 5.5 KB Excel file, created by Raymond Vera and last updated in 2026, uses agent-based modeling to help mission planners evaluate operational resilience.

Use Cases

• Evaluate team structure resilience based on simulated astronaut interactions.
• Analyze workload dynamics based on modeled cognitive skills and emotional states.
• Predict mission outcomes based on the interaction of personality traits and environmental factors.
• Plan for psychological well-being in isolated environments based on Monte Carlo simulation results.

Strengths

• Framework includes cognitive skills, emotional states, and personality traits for each agent.
• Simulations consist of tens of thousands of Monte Carlo iterations.
• Model is designed for specific, upcoming Artemis program missions (Artemis IV and V).
• Data is shared under a permissive CC-BY-4.0 license.

Limitations

• Dataset is very small at 5.5 KB, indicating limited scope.
• Row count and specific column-level documentation are unknown.
• Data is a simulation output, not empirical observations from real missions.

Provenance

Source

Raymond Vera via figshare

Collection Method

Created through agent-based modeling informed by literature on extreme environments, space analogs, and team science theories.

Time Range

Simulates scenarios for the upcoming Artemis IV and V missions.

Freshness

Last updated 2026-05-27 17:24:03

Geography

Lunar environment (Gateway and South Pole Base).