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✈️ Air traffic control simulation where agentic AI attempts to land airplanes

4 starsTypeScript

Agentic Airport

by ovisource·Mar 1, 2026·3 points·1 comment

AI Analysis

●●SolidWizardryBig BrainShip It

Single agent lands 6+ planes simultaneously using GPT-4o-mini. Collision avoidance works.

Strengths
  • Demonstrates genuine multi-object coordination without per-plane agents, which is non-obvious
  • Clear performance metrics and honest limitations (model strength, simulation speed impact)
  • Accessible browser-based demo with video proof, lower friction than academic papers
Weaknesses
  • Narrow use case—impressive technical feat but unclear practical application beyond exploration
  • Single-agent bottleneck acknowledged; multi-agent architecture would be more impactful but unimplemented
Category
Target Audience

AI researchers, game developers, simulation enthusiasts

Similar To

Game AI research projects · Multi-agent reinforcement learning simulations

Post Description

A browser based air traffic control simulation where agentic AI acts as a control tower with an objective of landing airplanes.

It was developed as an experiment in exploring agentic AI capabilities for controlling multiple objects in an active space.

The results were spectacular as a single agent can not only land multiple airplanes, but it also prevents collisions with other airplanes in small busy spaces.

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