Introduction: State or describe the problem to be solved.

For your reference, this section can cover the following points:

Design an agent, referred to as the maze problem$-$solver, which can be a mouse, a program, or a simulator, capable of efficiently finding an exit in any given maze configuration, the agent, equipped with algorithms, traverses the maze to locate an exit with minimal time span, measured in terms of the number grids traversed.

The input to the agent is any maze configuration. An agent program can be defined as an agent function, f: P$*->$ A$,$ where P$*$ represents every possible percept sequence and A represents a possible action. The agent$$s objective is to effectively map percept sequences to appropriate actions, enabling it to navigate through the maze toward an exit.

Describe the minimum of distinct grids in the given maze configuration, such that the distinct percepts with their states are finite. The minimum number of distinct grids in the maze configuration is determined to ensure a finite number of distinct percepts with their corresponding states. This ensures manageability and efficiency in processing the maze.

Describe the necessary and sufficient required actions for traversing the maze. Identify the essential actions necessary for navigating through the maze effectively. These actions should be sufficient to lead the agent from the entrance to the exit while accounting for various obstacles and challenges present in the maze.

Among various agent architectures including reflex with state, goal$-$based, utility$-$based, and learning models, describe which agent architecture would be used. Select and justify the most suitable agent architecture for the maze problem$-$solving task. Consider factors such as the complexity of the maze, the availability of information, and the desired level of adaptability and learning capability of the agent.

Graph$$s state search algorithms play a crucial role in finding the solution, which could be an optimal path from the initial node with a state to the goal node with a state in the maze. Discuss the application of various graph$$s state search algorithms such as breadth$-$first search, depth$-$first search, uniform cost search, and A$*$ search for this purpose, highlighting their advantages and limitations in the context of maze navigation.

What do you expect to solve the problem?

Provide an overview of the term project, including its objectives, scope, and expected deliverables. Summarize the key components of the project, such as designing the maze problem$-$solving agent, implementing algorithms, conducting experiments, and analyzing results.

Brief description of the content of the term project.

Graph Representation $$ A Search Graph

Formulate the problem as a labeled graph $($As $01).$

In this section, for your reference, you can address the following points to support

the obtained search graph, which is a labeled graph for the given maze configuration.

Develop a procedure for assigning minimal annotations, such as A$,$ B$,...,$ Z$,$ a$,$ b$,...,$ z$,$ r$1,$ g$1,$ g$2$ to certain grids of a given maze configuration, ensuring that these grids$$ annotations are necessary and sufficient. Based on these grids$$ annotations, construct a finite, undirected, and weighted graph from a given maze configuration. Does the obtained graph uniquely correspond to the given maze? Use the area of the grids labeled R$,$ C$,$ and Q in the given maze to justify the necessity and sufficiency of the grid annotations. Additionally, use the area of the grids, I, r$1,$ z$,$ o$,$ r$,$ v$,$ and q in the maze to further support the necessity and sufficiency of the grid annotations.

Describe the properties of the constructed labeled graph

The minimum number of nodes and edges, which are necessary and sufficient.

The equivalence of traversal between the graph and its associated given maze configuration

State Space Search Graph

Augment the labeled graph with a State Space Search graph $($As $02).$

For your reference, consider the following points.

Describe a finite set of states with actions for any given maze configuration $($Extend your work in As$02$ to the area of grids that covers the exits in the given maze$).$

Normalize a standard rule for specifying state representation for four perceived percepts within a grid using the inner states concept. Each percept is represented by a state which contains a $4-$tuple component described in Part I. What is the state representation for grids in which four sides of the grid are open?

Describe the state space search graph associated with the labeled graph $($As$02).$

For each node of the labeled graph, there corresponds to a state that contains four inner states, namely four $4-$tuple components.

For each edge of the labeled graph, there corresponds to an action or state.Actions. What is the state representation for two adjacent grids, each of the grids has four open sides. Describe the use of the state space search graph to verify verify the application of a se