This pseudocode is the basis for all graph search algorithms . Depending on the data structure used for the frontier and whether or not the cost model is taken into account, this basic algorithm can implement both uninformed and informed search. 1 place initial state on frontier 2 initialize explored list 3 while frontier is not empty 4 current-state := next state on frontier 5 return path( current-state) if is-terminal( current-state) 6 children := successors( current-state) 7 for each child in children 8 add child to frontier if not on explored or frontier 9 add current-state to explored 10 return nil However, pseudocode always leaves out the details. Here are a some you'll need to piece together: 1. If the algorithm is implemented as a function, what should the arguments be? If the algorithm is implemented as a method in a class, what else will the class need to provide? 2. How should the data structure for the frontier be specified? What are the easy ways to implement the functionality of a stack, queue and priority queue in Python? 3. The path() function (line 5) doesn't show how the solution is