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New LOLPlay benchmark tests AI agents in League of Legends

By PulseAugur Editorial · [1 sources] ·

A new benchmark called LOLPlay has been developed to evaluate real-time visual agents in the game League of Legends. The benchmark includes 36 champion-specific tasks covering resource management, combat, cooperation, and objectives. In evaluations of three models, GPT-6 Astra achieved the highest task success rate of 25.0% at low and medium effort settings. However, increasing reasoning effort did not improve performance for any model, and for GPT-6 Astra, it led to fewer interaction rounds, indicating a trade-off between reasoning depth and real-time control. AI

IMPACT This benchmark could drive advancements in real-time decision-making and visual reasoning for AI agents in complex, dynamic environments.

RANK_REASON The cluster describes a new benchmark and research paper on evaluating AI agents in a complex environment. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New LOLPlay benchmark tests AI agents in League of Legends

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The cluster describes a new benchmark and research paper on evaluating AI agents in a complex environment. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Zhaojian Yu ·

    LOLPlay: Benchmarking Real-Time Visual Agents in League of Legends

    arXiv:2611.03685v2 Announce Type: replace Abstract: Visual agents need to coordinate reasoning and action while their environment evolves during inference. We introduce LOLPlay, a benchmark in native League of Legends with 36 champion-specific tasks spanning resource management, …

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