You're pledging to donate if the project hits its minimum goal and gets approved. If not, your funds will be returned.
The aim is to give AI agents complete control of single nations within the simplistic kingdom sandbox of WorldBox, to study how AI agents behave when given complete control of a single nation with a unique religion, culture and way of life against other AI agents with the same nation.
To study how AI systems behave when given sustained, non-observable control of a complex simulated society.
Project Goals
.Building a working setup that allows AI agents to control kingdoms in a sandbox (using existing tools and modified platforms)
.Run a small number of simulations (target: 10–20 runs)
.Collect structured data on AI choices, diplomacy + military decisions/results, and long term outcomes
.Produce a public report with initial findings and justifications on either scaling up the study or ending it outright
HOW
.Adapt existing open tools (WorldBox-MCP, LLM agent loop) rather than building from scratch
.Bind individual AIs like Claude, Grok, ChatGPT, etc. to a single kingdom with full control and action space
.Analyze both quantitative metrics (survival, expansion, wealth, wars) and qualitative reasoning patterns
.Keep the initial pilot deliberately small so results can be inspected and improved
.hire a software developer: $9000 (bridge setup, mod configuration, multi-model agent loop, logging layer — 120 hrs at $75/hr)
.Hardware/materials: $700
.Data analyst: $3,200 (dataset construction, quantitative + qualitative analysis, conclusions)
.Game + mods: $50
.LLM API costs: $700
.Margin of error: $2,050
Total: $16,450
I am an independent researcher trying to explore practical ways to study AI agents, their thought processes and actions in a complex simulated environment. This is an early-stage project, and I am currently assembling the technical and analysis support needed.
I have no prior track record in published multi-agent experiments, but I have spent significant time researching existing tools (WorldBox-MCP, generative agents, AI-managed kingdom mods) and designing a plan to lower costs while keeping the research relevant.
Most likely causes of failure:
.Technical friction: WorldBox modeling/agent integration takes longer or is less stable than expected.
.Weak or repetitive AI behavior.
.Insufficient runs.
Outcomes if it fails:
.The technical setup and logging pipeline will still be documented and published.
.Even negative results are a useful signal for the field and will be included in the public report
.The research may not generate enough value to justify its continuation
I have raised around $1000 from the BOLA AHMED TINUBU STUDENT ASSOCIATION (BATSA) where I study as a political science researcher and I have also applied to other sources. In order to raise fund the research