diff --git a/README.md b/README.md index 2843545..a6ab00a 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,10 @@ -# Reinforcement Learning (RL) +> **Reinforcement Learning (RL)** brings Thompson Sampling multi-armed bandit A/B testing to Drupal, automatically optimizing content variants based on real user engagement without third-party services. Built by [DXPR](https://dxpr.com). +> +> [Getting Started](https://dxpr.com/c/getting-started) | +> [Pricing](https://dxpr.com/pricing) | +> [Try Free Demo](https://dxpr.com/try) + +# Reinforcement Learning (RL) - Adaptive A/B Testing for Drupal with Thompson Sampling Multi-armed bandit experiments in Drupal using Thompson Sampling algorithm for efficient A/B testing that minimizes lost conversions. @@ -424,11 +430,6 @@ RL provides optional cache management for web components: - Blocks displaying A/B tested content - Components needing frequent RL score updates -## Related Modules - -- [AI Sorting](https://www.drupal.org/project/ai_sorting) - Intelligent content - ordering for Drupal Views - ## Technical Implementation Full algorithm details available in source code: @@ -539,3 +540,13 @@ docker compose --profile lint run --rm drupal-check - [Thompson Sampling Paper](https://www.jstor.org/stable/2332286) - Original research - [Finite-time Analysis](https://homes.di.unimi.it/~cesa-bianchi/Pubblicazioni/ml-02.pdf) - Mathematical foundations + +--- + +## Related Modules + +- [RL Sorting](https://www.drupal.org/project/rl_sorting) - Views sort plugin that uses RL Thompson Sampling to order content by real engagement +- **RL Page Title** (bundled submodule) - A/B test page titles on any path, including nodes, Views displays, and custom controllers +- **RL Menu Link** (bundled submodule) - A/B test menu link labels for menu_link_content entities and YAML-defined links +- [Analyze](https://www.drupal.org/project/analyze) - Content analysis and quality scoring for Drupal +- [AI Content Strategy](https://www.drupal.org/project/ai_content_strategy) - AI-driven content strategy recommendations for Drupal diff --git a/docs/rl_project_desc.html b/docs/rl_project_desc.html index e96207e..231bc84 100644 --- a/docs/rl_project_desc.html +++ b/docs/rl_project_desc.html @@ -1,22 +1,26 @@

This module is included in DXPR CMS.

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The Reinforcement Learning (RL) module implements A/B testing in the most efficient and effective way possible, minizing lost conversions using machine learning.
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The Reinforcement Learning (RL) module implements A/B testing in the most efficient and effective way possible, minimizing lost conversions using machine learning.

Thompson Sampling is a learning-while-doing method. Each time a visitor lands on your site the algorithm "rolls the dice" based on what it has learned so far. Variants that have performed well roll larger numbers, so they are shown more often, while weak copies still get a small chance to prove themselves. This simple trick means the system can discover winners very quickly without stopping normal traffic.

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Traditional A/B tests run for a fixed horizon—say two weeks—during which half your visitors keep seeing the weaker version. Thompson Sampling avoids this waste. As soon as the algorithm has even a little evidence it quietly shifts most traffic to the better variant, saving conversions and shortening the wait for useful insights.

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Traditional A/B tests run for a fixed horizon (say two weeks) during which half your visitors keep seeing the weaker version. Thompson Sampling avoids this waste. As soon as the algorithm has even a little evidence it quietly shifts most traffic to the better variant, saving conversions and shortening the wait for useful insights.

For full details of what goes on behind the curtains check the source code: ThompsonCalculator.php.

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RL Modules

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RL Ecosystem

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RL is part of the DXPR marketing CMS stack, where it works alongside DXPR Builder and DXPR Theme to optimize content through automated experimentation.

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Features