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Superhuman AI agent dominates Generals.io using self-play RL

A new research paper details the creation of a superhuman AI agent for the real-time strategy game Generals.io. Trained for four days on high-end GPUs, the agent achieved the top rank among over 5,000 human players and demonstrated a significant win rate against the top human competitors. The development was enabled by a highly optimized JAX-native simulator that achieved speeds of tens of millions of frames per second, drastically reducing the data bottleneck for training. AI

IMPACT Demonstrates the effectiveness of self-play reinforcement learning and optimized simulators for achieving superhuman performance in complex strategy games.

RANK_REASON Research paper detailing a novel AI agent and its performance in a game.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Superhuman AI agent dominates Generals.io using self-play RL

COVERAGE [2]

  1. arXiv cs.LG TIER_1 English(EN) · Martin Schmid ·

    Superhuman AI for Generals.io Using Self-Play Reinforcement Learning

    We present a superhuman AI agent for Generals.io, a real-time strategy game that requires both long-horizon planning and short-term tactics under strong imperfect information. Trained for four days on 4x NVIDIA H200 GPUs, our agent reaches #1 on the public 1v1 leaderboard of over…

  2. r/MachineLearning TIER_1 English(EN) · /u/shrekofspeed ·

    I made a superhuman Generals.io agent with self-play RL [P]

    <!-- SC_OFF --><div class="md"><p>Hi everyone,</p> <p>I trained a self-play RL agent for <a href="http://Generals.io">Generals.io</a> that reached superhuman-level and ranked #1 on the human 1v1 leaderboard.</p> <p>It began as my master's thesis where the goal was to beat a prior…