Update default.html

Author: sichkar-valentyn

docs/_layouts/default.html

@@ -28,8 +28,9 @@
     <div id="header_wrap" class="outer">
         <header class="inner">
           <a id="forkme_banner" href="https://github.com/sichkar-valentyn/Reinforcement_Learning_in_Python">View on GitHub</a>
+          <img src="/Reinforcement_Learning_in_Python/images/Valentyn_Sichkar.png" alt="Valentyn Sichkar" width="150" height="150" />
 
-          <img alt="" width="230" height="230" class="avatar width-full rounded-2" src="https://avatars3.githubusercontent.com/u/34546286?s=460&amp;v=4" /></a>
+          <img alt="" width="230" height="230" class="avatar width-full rounded-2" src="https://avatars3.githubusercontent.com/u/34546286?s=460&amp;v=4" />
 
           <h1 id="project_title">Reinforcement Learning in Python</h1>
           <h2 id="project_tagline">Implementing Reinforcement Learning, namely Q-learning and Sarsa algorithms, for global path planning of mobile robot in unknown environment with obstacles. Comparison analysis of Q-learning and Sarsa</h2>
@@ -131,7 +132,7 @@ <h2 id="content">Content</h2>
 <h3 id="rl-q-learning-environment-1-experimental-results"><a name="RL Q-Learning Environment-1. Experimental results">RL Q-Learning Environment-1. Experimental results</a></h3>
 <p>Environment-1 with mobile robot, goal and obstacles</p>
 
-<p><img src="/Reinforcement_Learning_in_Python/images/Environment-1.gif" alt="Environment-1" width=312 height=341 />  <img src="/Reinforcement_Learning_in_Python/images/Environment-1.png" alt="Environment-1" width=312 height=341 /></p>
+<p><img src="/Reinforcement_Learning_in_Python/images/Environment-1.gif" alt="Environment-1" width="312" height="341" />  <img src="/Reinforcement_Learning_in_Python/images/Environment-1.png" alt="Environment-1" width="312" height="341" /></p>
 
 <h3 id="q-learning-algorithm-resulted-chart-for-the-environment-1"><a name="Q-learning algorithm resulted chart for the environment-1">Q-learning algorithm resulted chart for the environment-1</a></h3>
 <p>Represents number of episodes via number of steps and number of episodes via cost for each episode</p>