Fix typo in Reinforcement Learning Tips and Tricks page (#711)

* Fix typo in rl_tips.rst

* Update changelog.rst

* Add username to contributors in changelog.rst

docs/guide/rl_tips.rst

@@ -56,7 +56,7 @@ That's why most of the successes in RL were achieved on games or in simulation o
 As a general advice, to obtain better performances, you should augment the budget of the agent (number of training timesteps).
 
 
-In order to to achieved a desired behavior, expert knowledge is often required to design an adequate reward function.
+In order to achieve the desired behavior, expert knowledge is often required to design an adequate reward function.
 This *reward engineering* (or *RewArt* as coined by `Freek Stulp <http://www.freekstulp.net/>`_), necessitates several iterations. As a good example of reward shaping,
 you can take a look at `Deep Mimic paper <https://xbpeng.github.io/projects/DeepMimic/index.html>`_ which combines imitation learning and reinforcement learning to do acrobatic moves.
 

docs/misc/changelog.rst

@@ -63,6 +63,7 @@ Documentation:
 - Add dedicated page for callbacks
 - Fixed example for creating a GIF (@KuKuXia)
 - Change Colab links in the README to point to the notebooks repo
+- Fix typo in Reinforcement Learning Tips and Tricks page. (@mmcenta)
 
 
 Release 2.9.0 (2019-12-20)
@@ -629,4 +630,4 @@ Thanks to @bjmuld @iambenzo @iandanforth @r7vme @brendenpetersen @huvar @abhiskk
 @XMaster96 @kantneel @Pastafarianist @GerardMaggiolino @PatrickWalter214 @yutingsz @sc420 @Aaahh @billtubbs
 @Miffyli @dwiel @miguelrass @qxcv @jaberkow @eavelardev @ruifeng96150 @pedrohbtp @srivatsankrishnan @evilsocket
 @MarvineGothic @jdossgollin @SyllogismRXS @rusu24edward @jbulow @Antymon @seheevic @justinkterry @edbeeching
-@flodorner @KuKuXia @NeoExtended @solliet
+@flodorner @KuKuXia @NeoExtended @solliet @mmcenta