Consider the problem of developing $($designing and implementing$)$ an intelligent agent called the maze problem$-$solver $($or called a mouse, an agent$).$Given ANY maze configuration, the maze has an entrance gate $($equivalently$,$ called the initial state$)$ for entering the maze and two exit gates, g$1,$ and g$2($or called final states$).$ The maze problem$-$solver can find its way from an entrance $[]$ to an exit $][.$ The goal is that the maze problem$-$solver enters the given maze and finds a way to exit the maze with a minimal time span $($in terms of the number of squares traversed$).$ A maze configuration is given at the end of this assignment. We will continue to use this maze configuration for the remaining assignments $($i$.$e$.,$ project$).$ This project is to program an agent called the maze problem$-$solver, which will run around any given maze to find its way out from an exit gate. We will address the maze configuration and its representation later, which couldserve as input to the program. Q$1$:An agent program can be defined as an agent function, f: P$*->$ A$,$ which maps every possible percept sequence to a possible action the agent can perform.Assume that the state representation for each of the grids is as follows: Let the wall line $($obstacle$)$ have the value $1,$ the grid line $($open$)$ is $2,$ and the exit line $($with a gate$)$ is $0.$ For each grid, we will use these values to describe the four sides of any grid: the top $($the head of the agent$),$ the right, the bottom $($its tail$),$ and the left. At any grid, a corresponding percept can be represented at In$($t$,$ r$,$ b$,$ l$)$ to form a state $[$t$,$ r$,$ b$,$ l$].$ This also coincides with the fact that the head of the agent is pointing to the top of a grid, and the agent's tail is pointing at the bottom of the grid square. The specification of a percept and its state is a one$-$to$-$one correspondence. For example, if the agent enters the entrance gate, the agent is in the first grid, say Athe percept for the grid can be represented as In$($A$),$ which is In$(2,2,0,1).$ The state$$s specification of the percept In$(2,2,0,1)$ is $[2,2,0,1].$ Therefore, it suffices to use the state$$s specification $[$t$,$ r$,$ b$,$ l$]$ to represent the percept In$(2,2,0,1).$ For this reason, we will use the state$$s specification to represent states and percepts. If we use In$($A$)$ as an initial state, then the state can be described as $[2,2,0,1].$ However, if we insist the agent should be outside the maze facing the entrance, then the initial state $[0,-,-,-]$ or $[0,2,2,2]$ where the precept is In$(0,-,-,-)$ or In$(0,2,2,2),$ respectively. All these descriptions are consistent with the Simple$-$ReflexAgent$($percept$).$ It states state $$ INTERPRET$\_$INPUT$($percept$)$ where percept is the grid's physical configuration generated by the agent sensor$.$ It means that the image is converted into a program variable, state, using the function INTERPRET$\_$INPUT. The agent has three actions: rightTurn, leftTurn, and forward. The rightTurn $($R$)$ within a grid is defined as follows: rightTurn$($In$(2,2,0,1),$ In$(2,0,1,2)).\{$brings the first to last; in fact. $$In$$ can be omitted$\}$ This means the agent is first in a grid heading in a direction. The right$-$turn action enables the agent to remain in the same grid, but the agent turns right, heading in a new direction that is perpendicular to the initial direction. Pictorially,Using the state$$s specifications, it is rightTurn$([2,2,0,1],[2,0,1,2]),$ or R$[2,2,0,1]->[2,0,1,2].$he leftTurn$($L$)$ within a grid is defined as follows:

leftTurn$($In$(2,2,0,1),$ In$(1,2,2,0).\{$brings the last component to be first$\}$

This means the leftTurn action enables the agent to remain in the same grid but in a new direction of the agent that is perpendicular to the previous $($initial$)$ direction and faces to the left side of the initial direction.Using the state$$s specifications, it is leftTurn$([2,2,0,1],[1,2,2,0],$ or L $[2,2,0,1]->[1,2,2,0]$The forward $($F$)$ for two adjacent grids is defined as follows:For the following pictorial example, we can describe the agent forwards from one grid to another grid with different percepts. This first parameter describes that the agent is in the first grip and then goes into the other grip with two walls and two grid lines. We use forward action to describe the following: forward$($In$(2,2,0,1),$ In$(2,1,2,1))$Using the state$$s specifications, it is forward$([2,2,0,1],[2,1,2,1],$ or F $[2,2,0,1]->[2,1,2,1]$ Using the above description, give$/$describe your proposed percepts and actions. $($Warning:the later assignments will be based on your previous work! Therefore, a good and detailed work would help you with the rest of your entire project $($i$.$e$.,$ assignments$).($a$)$ How many different configurations of grids are in the given maze?$($b$)$ How many different actions are based on the given maze?$($c$)$ Specify its state description corresponding to each of the distinct grids.