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Grammatical evolution and Q-learning

Grammatical evolution + Q-learning

1 paper tagged archive 2025-07-28

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

This method works as a two-levels optimization algorithm. The outmost layer uses Grammatical evolution to evolve a grammar to build the agent. Then, Q-learning is used the fitness evaluation phase to allow the agent to learn to perform online learning.

Source: Evolutionary learning of interpretable decision trees

Papers archive 2025-07-28

1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

5 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Evolutionary Algorithms1
OpenAI Gym1
Reinforcement Learning1
Reinforcement Learning (RL)1
reinforcement-learning1

Usage over time archive 2025-07-28

Papers per year tagged with Grammatical evolution + Q-learning: 2020 to 2020, peak 1 1 0 2020: 1 paper 2020
Papers per year the archive tags with this method, by the paper's archive date (1 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Optimization

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