AI TraceTrace Foundation, Inc.
Data Analysis

Reviewed and published by trentmaziarz, April 22, 2026. Discovered and drafted by our automated research pipeline.

Riot Games uses deep reinforcement learning to help game designers analyze and test game balance in Legends of Runeterra before content is released to players, giving designers a tool to predict whether new cards or mechanics will be overpowered or underpowered.

Details

Riot trained a reinforcement learning agent that plays Legends of Runeterra against itself at scale to discover which decks and cards are consistently dominant or weak, producing balance scores that became part of game designers' key performance indicators. The agent's predicted balance scores were found to match design intuition and correctly predicted which decks were strongest, with directional alignment confirmed against live player data. This was Riot's first major productionized use of deep reinforcement learning for game balance and has since been extended to additional game titles.

Products affected

Legends of Runeterra

Sources & Evidence

Cite this record

Trace Foundation. (2026). Riot Games: Riot Games uses deep reinforcement learning to help game designers analyze and test game balance in Legends of Runeterra before content is released to players, giving designers a tool to predict whether new cards or mechanics will be overpowered or underpowered (data as of 2026-04-22) [Data set record]. AI Trace. https://www.aitrace.org/r/practice/b4351981-c321-403e-bc25-438f5af776c7. Accessed September 11, 2026.

Stable link
https://www.aitrace.org/r/practice/b4351981-c321-403e-bc25-438f5af776c7
Data as of
April 22, 2026
Last verified
April 22, 2026

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