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The   reflex agents  are known as the simplest agents because they directly map states into actions. Unfortunately, these agents fail to operate in an environment where the mapping is too large to store and learn.   Goal-based agent,  on the other hand, considers future actions and the desired outcomes. Here, we will discuss one type of goal-based agent known as a  problem-solving agent , which uses atomic representation with no internal states visible to the problem-solving algorithms. Problem-solving agent The problem-solving agent perfoms precisely by defining problems and its several solutions. According to psychology, “ a problem-solving refers to a state where we wish to reach to a definite goal from a present state or condition.” According to computer science,  a problem-solving is a part of artificial intelligence which encompasses a number of techniques such as algorithms, heuristics to solve a problem. Therefore, a problem-solving agent is a ...

  Breadth-first search (BFS) It is a simple search strategy where the root node is expanded first, then covering all other successors of the root node, further move to expand the next level nodes and the search continues until the goal node is not found. BFS  expands the shallowest (i.e., not deep) node first using FIFO (First in first out) order. Thus, new nodes (i.e., children of a parent node) remain in the queue and old unexpanded node which are shallower than the new nodes, get expanded first. In BFS, goal test  (a test to check whether the current state is a goal state or not)  is applied to each node at the time of its generation rather when it is selected for expansion. Breadth-first search tree In the above figure, it is seen that the nodes are expanded level by level starting from the root node  A  till the last node  I  in the tree. Therefore, the BFS sequence followed is:  A->B->C->D->E->F->G->I . BFS Algorith...