Update Readme

README.md

@@ -63,10 +63,10 @@ AI Behavior
 Found in main.py
 
 <ul>
-<li>Wander<span>The nodes move at a constant speed and do self-rotations. It is in the state “Im_not_it”. In the game the node will be highlighted in the color “blue”. Function: def _steerForWander(self,dt):</span></li>
-<li>Evade<span>If a node that is in a state of “Im_not_it” is approached by a certain distance by a node that is in the state “Im_it”, then it will interact with other nodes and start the evade process where it will move at a faster speed than the ‘Wander’ constant speed to run away from the “seeker”. If a node was approached by the seeker but then the seeker was seeking another node, then it will be in the state of ‘Evade’ but switch back to the “Wander” state. In the game the node will be highlighted in the color “blue”. Function: def _steerForFlee(self,dt)</span></li>
-<li>Seek<span>The node that is in the state of “Im_it” generally is in the ‘SEEK’ behavior. Here the node moves at a speed faster than the constant wander speed and interacts with other nodes based on their distance and which node to choose to seek and follow in order to tag. If the seeker finds another node closer to it while seeking then it reroutes its path and start seeking the other node. In the game the node will be highlighted in the color “red”. If it just got tagged, during that instant, it will turn from “blue” to “green” then to “red”. Function: def _steerForSeek(self,dt):</span></li>
-<li>Herding<span>The node that is in the state of “iAmALeader” generally is in the ‘WANDER’ behavior. Here the node moves at a constant speed and does self-rotations and interacts with the seekers based on their distance through the calculated nodepaths in order to evade them as best as possible. In the game the node will be highlighted in the color “pink”. If it just got tagged, during that instant, it will turn from “pink” to “green” then to “red”. The follower node in the state of “setLeader” is assigned as the weak member in order to find a leader. The node will be at a wander state. Once it approaches a leader, it will start following it in order to best avoid the seekers since the leader has a better strategy at evading seekers.</span></li>
+<li><b><i>Wander: </i></b><span>The nodes move at a constant speed and do self-rotations. It is in the state “Im_not_it”. In the game the node will be highlighted in the color “blue”. Function: def _steerForWander(self,dt):</span></li>
+<li><b><i>Evade: </i></b><span>If a node that is in a state of “Im_not_it” is approached by a certain distance by a node that is in the state “Im_it”, then it will interact with other nodes and start the evade process where it will move at a faster speed than the ‘Wander’ constant speed to run away from the “seeker”. If a node was approached by the seeker but then the seeker was seeking another node, then it will be in the state of ‘Evade’ but switch back to the “Wander” state. In the game the node will be highlighted in the color “blue”. Function: def _steerForFlee(self,dt)</span></li>
+<li><b><i>Seek: </i></b><span>The node that is in the state of “Im_it” generally is in the ‘SEEK’ behavior. Here the node moves at a speed faster than the constant wander speed and interacts with other nodes based on their distance and which node to choose to seek and follow in order to tag. If the seeker finds another node closer to it while seeking then it reroutes its path and start seeking the other node. In the game the node will be highlighted in the color “red”. If it just got tagged, during that instant, it will turn from “blue” to “green” then to “red”. Function: def _steerForSeek(self,dt):</span></li>
+<li><b><i>Herding: </i></b><span>The node that is in the state of “iAmALeader” generally is in the ‘WANDER’ behavior. Here the node moves at a constant speed and does self-rotations and interacts with the seekers based on their distance through the calculated nodepaths in order to evade them as best as possible. In the game the node will be highlighted in the color “pink”. If it just got tagged, during that instant, it will turn from “pink” to “green” then to “red”. The follower node in the state of “setLeader” is assigned as the weak member in order to find a leader. The node will be at a wander state. Once it approaches a leader, it will start following it in order to best avoid the seekers since the leader has a better strategy at evading seekers.</span></li>
 </ul>
 
 Constraints
@@ -150,7 +150,7 @@ SLAM
 
 Found in slam.py and onlineslam.py
 
-The Graph SLAM algorithm is used for Simultaneous Localization and Mapping to build 2-D or 3-D maps. This is an on-going research topic. It is used in the Google Self-Driving Car car. It will use localization and mapping to create a 2-D or 3-D map of the environment to know where it is and where and how it should navigate to.
+The Graph SLAM algorithm is used for Simultaneous Localization and Mapping to build 2-D or 3-D maps. This is an on-going research topic. It is used in the Google Self-Driving Car. It will use localization and mapping to create a 2-D or 3-D map of the environment to know where it is and where and how it should navigate to.
 
 Thank You
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