AHL paradigm proposed and AAArena benchmark released
What happened
Paper author Kaisen Yang proposes the Adversarial Heuristic Learning paradigm and releases AAArena, an adversarial game agent benchmark. The benchmark contains 12 real adversarial games and 1,920 archived human programs, and uses an evaluation protocol modeled on real game competitions to examine agents' learning ability in long-running competitions. The paper reports that among the evaluated model and tool configurations, Opus5.5 paired with Claude Code took 6 gold medals, while no configuration was able to conquer the remaining 6 human ladders.
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- arXiv Game AIPickCan AI agents learn their way to the top? AAArena evaluates heuristic learning in a long-running game competition
The paper proposes the AAArena benchmark, using 12 real adversarial games and 1,920 archived human programs to evaluate agents' learning ability in long-running competitions. Among the evaluated model and tool configurations, Opus5.5 with Claude Code took 6 gold medals, and no configuration could take the remaining 6 human ladders.
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