TowerMind: A lightweight tower-defense testbed for AI agents
TowerMind is a new, lightweight tower-defense game environment for testing AI agents, especially large language models (LLMs), on planning and decision-making.
- Low compute cost and easy to run
- Multimodal observations: pixels, text, and structured game state
- Customizable levels and rules
- Built-in tests for model hallucination
The authors create five benchmark levels and evaluate popular LLMs under different input settings, plus classic RL baselines (Ape-X DQN and PPO). Results show a clear gap to human experts. Common failure modes include weak plan validation, single-track choices (lack of multifinality), and inefficient action use.
Why it matters: RTS-style games demand both long-term strategy and quick tactical moves—perfect for probing agent skills. TowerMind offers a practical, open benchmark that complements heavier RTS testbeds.
Read more: https://arxiv.org/abs/2601.05899 Code: https://github.com/tb6147877/TowerMind
Paper: https://arxiv.org/abs/2601.05899v1
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