C++ Vector Maze.

Place an agent in 1 dimensional maze( intialize agent in a random position), the 1d maze can be of any size you can do 10 for example, have the agent go thru the maze until it finds the exit/finsihes the maze , once the agent gets to the goal it should get rewarded.

Additonally After you have that working instead of having the agent randomly make it thru the maze set up a value function V(s) = r(s) + GAMMA V(s+1),

using the value function and reward function , you can set those as additonal maze with its index holding values that get higher as you get to the goal, find a way to get out the maze optimally instead of randomly.

so first we are going to randomly have the agent go thru the maze until it finds the exit/finsihes the maze , once the agent gets to the goal it should get rewarded, then we will set it up again but this time using a value function (reinforcement learning).