Update dependencies (#23)

* finish Chapter1

* add Chapter 02

* add part of Chapter06

* add more notebooks

* add Chapter08_Maze.jl

* sync local work

* sync local changes

* sync local notebooks

* use ReinforcementLearning@v0.8.0

Author: findmyway

Manifest.toml

@@ -1,30 +1,9 @@
-name = "ReinforcementLearningAnIntroduction"
-uuid = "02c1da58-b9a1-11e8-0212-f9611b8fe936"
-authors = ["TianJun <tianjun.cpp@gmail.com>"]
-version = "0.2.2"
-
 [deps]
-DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
-LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-MacroTools = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
-Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
-ReinforcementLearningBase = "e575027e-6cd6-5018-9292-cdc6200d2b44"
-ReinforcementLearningCore = "de1b191a-4ae0-4afa-a27b-92d07f46b2d6"
-SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
+PlutoUI = "7f904dfe-b85e-4ff6-b463-dae2292396a8"
+ReinforcementLearning = "158674fc-8238-5cab-b5ba-03dfc80d1318"
+Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 StatsPlots = "f3b207a7-027a-5e70-b257-86293d7955fd"
-
-[compat]
-DataStructures = "0.17"
-Distributions = "0.22"
-Flux = "0.10"
-MacroTools = "0.5"
-Plots = "0.29"
-Reexport = "0.2"
-StatsBase = "0.32"
-StatsPlots = "0.12"
-julia = "1.4"

Project.toml

@@ -17,4 +17,28 @@
     </a>
 </p>
 
-This repo contains most of the reinforcement learning environments referred in the book [Reinforcement Learning: An Introduction(2nd)](http://incompleteideas.net/book/the-book-2nd.html). The code to generate those figures are in the `notebooks` folder. Try it interactively on [MyBinder](https://mybinder.org/v2/gh/JuliaReinforcementLearning/ReinforcementLearningAnIntroduction.jl/master) now! 
+This project provides the [Julia](https://www.julialang.org/) code to generate figures in the book
+[Reinforcement Learning: An
+Introduction(2nd)](http://incompleteideas.net/book/the-book-2nd.html). One of
+our main goal is to help users understand the basic concepts of reinforcement
+learning from an engineer's perspective. Once you have grasped how different
+components are organized, you're ready to explore a wide variety of modern deep
+reinforcement learning algorithms in [ReinforcementLearningZoo.jl](https://github.com/JuliaReinforcementLearning/ReinforcementLearningZoo.jl).
+
+## How to use?
+
+If you are new to Julia, you can open the notebooks and play interactively at
+[TODO: insert mybinder url] or preview the generated `pdf` files under the
+`previews` folder.
+
+For experienced users with the latest stable Julia properly installed:
+
+1. Clone this project.
+1. Start the Julia REPL under the folder you created above.
+1. Install [Pluto.jl](https://github.com/fonsp/Pluto.jl)
+  1. `] add Pluto`
+  1. `using Pluto`
+  1. `Pluto.run()`
+1. Now you can see the Pluto page is opened in your browser. Paste
+   `notebooks/Chapter01_Tic_Tac_Toe.jl` (or any other file under the `notebooks` folder) into
+   the input box and click the `Open` button.