This project Divided into 4 Stages:
Stage#1:
• Problem definition and planning.
• Environment type.
• Agent type.
• PEAS (Performance measure, Environment, Actuators, Sensors).
Stage#2:
• Problem state space (State graph and/or State tree).
• Initial state.
• Goal test to verify reaching goal state.
• Successor function with (Set of actions & Paths costs).
• Transition model.
• A solution / plan to show the transformation from initial state to goal state.
• UML diagrams if there is a need for it
Stage#3: ● Describe any information & assumptions needed to apply A* on your case study, for example describe on what logical basis you assumed or calculated the heuristic function(s).
● Apply A* search algorithm on the state diagram and / or state tree with initial state and goal state with respect to your case study (on paper or electronic document).
● Note if your case study has multiple objectives choose one of them that you can achieve by apply search.
Stage#4: ● Implementation should be on MATLAB or Python only.
● Implement A* search with dynamic input parameters for both initial state and goal state.
● Print the trajectory path of nodes (Solution / plan), after the execution of the algorithm.
● According to result you get from your code, illustrate from your own point of view if A* was useful or not to solve your problem.
● Adding GUI (Interactive animations, game interface…etc.).