From a Search Graph Augmented with State Space Search Graph to Search Tree Construct A$*$ or Iterative Deepening A$*($IDA$*),$ but not both. The agent consisting algorithms that traverse a given maze to find an exit. Tree or graph search algorithms for finding the solution are a path from the initial node to the goal node. For your reference, address the following points $-->$Design a general tree search algorithm, a best$-$first strategy A$*$ or IDA$*$ for traversing a given maze configuration to find an exit, with the help from the search graph obtained in Section II$.-->$Define Evaluation function f$($n$)=$ g$($n$)+$ h$($n$)-->$g$($n$)=($actual$)$ cost to reach state n $($from the initial state$).-->$h$($n$)=$ estimated cost $($distance$)$ from state n to closest goal. $-->$Describe that A$*$ or IDA$*$ use an admissible and consistent heuristic in addition to the actual cost to reach state n from the initial state. $-->$Assign g$($n$)$ and h$($n$)$ with cost values for each of the grids$/$nodes of the given maze configuration $-->$Discuss conditions for the optimality: admissibility and consistency $-->$Based on the search graph of the given maze configuration, give a few examples for demonstrating using A$*$ or IDA$*$ search on the labeled graph $-->$Is the A$*$ or IDA$*$ search technique complete, optimal, and heuristic? Justify your claims. $-->$What is A$*$ search technique time$-$efficient, and space$-$efficient? $($Justify your claims$).-->$What is the goal test?