From 3fd0bf4f0fd65d7e7c68e6eceae9a2038129e7b9 Mon Sep 17 00:00:00 2001
From: Itai Caspi <30383381+itaicaspi-intel@users.noreply.github.com>
Date: Sun, 26 Aug 2018 12:09:46 +0300
Subject: [PATCH] Update README.md
---
README.md | 12 ++++++++----
1 file changed, 8 insertions(+), 4 deletions(-)
diff --git a/README.md b/README.md
index b817817..6eb9b58 100644
--- a/README.md
+++ b/README.md
@@ -17,11 +17,11 @@ Training an agent to solve an environment is as easy as running:
coach -p CartPole_DQN -r
```
-
+
-
+
-
+
Blog posts from the IntelĀ® AI website:
@@ -34,6 +34,7 @@ Contacting the Coach development team is also possible through the email [coach@
- [Coach](#coach)
* [Overview](#overview)
+ * [Benchmarks](#benchmarks)
* [Documentation](#documentation)
* [Installation](#installation)
+ [Coach Installer](#coach-installer)
@@ -46,6 +47,10 @@ Contacting the Coach development team is also possible through the email [coach@
* [Citation](#citation)
* [Disclaimer](#disclaimer)
+## Benchmarks
+
+One of the main challenges when building a research project, or a solution based on a published algorithm, is getting a concrete and reliable baseline that reproduces the algorithm's results, as reported by its authors. To address this problem, we are releasing a set of [benchmarks](benchmarks) that shows Coach reliably reproduces many state of the art algorithm results.
+
## Documentation
Framework documentation, algorithm description and instructions on how to contribute a new agent/environment can be found [here](https://nervanasystems.github.io/coach/).
@@ -286,7 +291,6 @@ dashboard
* [Bootstrapped Deep Q Network](https://arxiv.org/abs/1602.04621) ([code](rl_coach/agents/bootstrapped_dqn_agent.py))
* [UCB Exploration via Q-Ensembles (UCB)](https://arxiv.org/abs/1706.01502) ([code](rl_coach/exploration_policies/ucb.py))
-
## Citation
If you used Coach for your work, please use the following citation: