RL-Ai-Player

This is a exporation projection for classical reinforcement learning.
The Algorithm we will be implemented are here

GYM starting

to build all the images docker-compose bulid
to run all the container run docker-compose up -d
check for the tokens of jupyter notebook tokens with running docker-compose logs notebook to obtain ?token=SOME_HASH_STRING
and visit localhost:8888?token=THE_TOKENS_THAT_SHOWN_IN_TERMINAL with your browser

Testing MDD with flink with docker compose

MapReduce Algorithm Steps

Map Function
- Splitting
  - Splitting Step takes input DataSet from Source and divide into smaller Sub-DataSets.
- Mapping
  - Mapping Step takes those smaller Sub-DataSets and perform required action or computation on each Sub-DataSet
- This would finally pairs as <Key,Value> as output
- Input: DataSets and Output List of <Key,Value>
Shuffle Function
- Shuffling Function can explains as combine function
- Merging combining all Key-Value pairs which have the same key and return <Key, List<Value>>.
- Sorting based Key from aboved.
Reduce Function
- Reduced Function Output generate List of <Key,Value>.