Real-Data Environment
Real-Data Environment: Unlike synthetic AI benchmarks, Tokyo Risk grounds every experiment in reality.
Core trick
Feeds Google Routes API traffic times into battle penalties, and has Gemini rewrite each player's agent prompt and tool set after every match.
Description
Real-Data Environment: Unlike synthetic AI benchmarks, Tokyo Risk grounds every experiment in reality. Google Places API feeds Tokyo's 23 wards , while Google Routes API injects real traffic conditions as dynamic combat penalties. Agents reason about a city that actually exists.
Autonomous Online Learning Loop: Each player deploys 10 agents configured with custom system prompts, tool selections, and multi-agent coordination strategies. After each battle, results feed back into an automated optimization cycle—Gemini analyzes outcomes, generates improved configurations, and reruns the experiment automatically. The system answers: "What prompt, tool, and agent strategy actually wins on real Tokyo geography?" Voice-Driven Sub-Commander: A sub-commander layer bridges human intent and agent execution via voice. Speak a command and Gemini parses it through Function Calling into live agent directives.
The linked repo returns 404, so it was deleted or made private.