Add step-by-step and pipeline tutorials for reinforcement learning with Vertex AI.

tutorials/community/reinforcement_learning/README.md

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+# Reinforcement Learning Protytopes on Vertex AI
+
+This directory demos the use of TF-Agents, Kubeflow Pipelines (KFP) and Vertex
+AI in building reinforcement learning applications. The RL applications we build
+are movie recommendation systems based on the MovieLens 100K dataset.
+
+There are 2 demos:
+
+1.  Step-by-step demo: showcase how to use custom training, custom
+    hyperparameter tuning, custom prediction and endpoint deployment of Vertex
+    AI to build a RL movie recommendation system
+
+2.  End-to-end pipeline demo: showcase how to build a RL-specific MLOps pipeline
+    using KFP and Vertex Pipelines, as well as additional Vertex AI and GCP
+    services such as BigQuery, Cloud Functions, Cloud Scheduler, Pub/Sub.
+    Highlights of this end-to-end pipeline are:
+
+    -   RL-specific implementation for training and prediction
+    -   Simulation for initial training data, prediction requests and
+        re-training
+    -   Closing of the feedback loop from prediction results back to training
+    -   Customizable and reproducible KFP components
+
+Each demo contains a notebook that carries out the full workflow and user
+instructions, and a `src/` directory for Python modules and unit tests.