  A robot finds it really hard to learn creatively and adapt to new unseen
challenges. This is mainly because of the minimal information it has access to
or experience towards. Paulius et al. [1] presented a way to construct
functional graphs that encapsulate. Sakib et al. [2] further expanded FOON
objects for robotic cooking. This paper presents a comparative study of Breadth
First Search (BFS), Greedy Breadth First search (GBFS) with two heuristic
functions, and Iterative Depth First Search (IDFS) and provides a comparison of
their performance.
