diff --git a/week3/material/agent_programs.py b/week3/material/agent_programs.py
index e689ec26e38836082c6ecdb40141a645e8795ebb..bdb3690ccbd50f1db6c4fce01761956c34487030 100644
--- a/week3/material/agent_programs.py
+++ b/week3/material/agent_programs.py
@@ -10,26 +10,6 @@ from vacuum_agent import VacuumAgent
 
 DIRECTIONS = VacuumAgent.WHEELS_DIRECTIONS
 
-"""
-Agent implementing a search algorithm:
-- The agent must first update the model of the world (a GridMap) with the following information:
-    1. The current tile set as visited ('X')
-    2. The location of the charging dock ('C') given by the sensor 'charging-dock-location-sensor'
-    3. Any wall the agent crashed against ('W')
-    4. The dirt in the adjacent cells ('D')
-- The agent must start cleaning if it is not currently doing so and stop cleaning if 
-the whole environment has been cleaned
-- The agent must activate the suction mechanism if there is dirt on the current tile
-or deactivate it if there is not (to preserve the battery)
-- Then, the agent must check the current battery level:
-    1. If the battery level is below 50%, the agent must use a search algorithm to 
-    head back to the charging dock before getting out of battery
-    2. Otherwise, the agent must use a search algorithm to head to an unvisited
-    tile
-    In both cases, the agent will return an action to change the direction of the
-    wheels towards the goal state, based on the path found by the search algorithm
-"""
-
 # 1. We create a model of the environment using a GridMap
 # this step is similar to Week 2 workshop when implementing
 # the model based agents
diff --git a/week3/solution/agent_programs.py b/week3/solution/agent_programs.py
index 64892d160acb89f716c539001c411ce1c0b7e24c..08ca5504b67660432d12e119679aa76270b19a37 100644
--- a/week3/solution/agent_programs.py
+++ b/week3/solution/agent_programs.py
@@ -10,26 +10,6 @@ from vacuum_agent import VacuumAgent
 
 DIRECTIONS = VacuumAgent.WHEELS_DIRECTIONS
 
-"""
-Agent implementing a search algorithm:
-- The agent must first update the model of the world (a GridMap) with the following information:
-    1. The current tile set as visited ('X')
-    2. The location of the charging dock ('C') given by the sensor 'charging-dock-location-sensor'
-    3. Any wall the agent crashed against ('W')
-    4. The dirt in the adjacent cells ('D')
-- The agent must start cleaning if it is not currently doing so and stop cleaning if 
-the whole environment has been cleaned
-- The agent must activate the suction mechanism if there is dirt on the current tile
-or deactivate it if there is not (to preserve the battery)
-- Then, the agent must check the current battery level:
-    1. If the battery level is below 50%, the agent must use a search algorithm to 
-    head back to the charging dock before getting out of battery
-    2. Otherwise, the agent must use a search algorithm to head to an unvisited
-    tile
-    In both cases, the agent will return an action to change the direction of the
-    wheels towards the goal state, based on the path found by the search algorithm
-"""
-
 # 1. We create a model of the environment using a GridMap
 # this step is similar to Week 2 workshop when implementing
 # the model based agents