One of the major risks with greedy heuristics isa; they can take arbitrarily long to completeb. they can get stuck on a local maximum $.$ they can get stuck in cyclesd. they provide too many optionse. they can get stuck in a minimum when a maximum is desiredBidirectional search can be much faster than either BFS or DFS$.$ Why isn't it the default search method?a$.$ It can only be applied to particularly large search spacesb. It is complete, but not optimalc. It is optimal, but not completed. It doesn't efficiently utilize storage e$.$It is not complete or optimalIterative depth$-$first search $($ID$-$DFS$]$ requires re$-$creating search nodes that are near the root of the search path. Why is this redundancy considered acceptable?a$.$If the branching factor is high, this is a small proportion of all nodes and so not significant b$.$Only a few such redundant nodes are in existence at any one timec. There is a strict upper bound on the number of times each such node must be re$-$createdd. Memory is selectively released at the end of each cyclee. None of these are correct.Turing's breakthrough paper on the foundations of Al hypothesized that.Al would make human intelligence obsoleteb. Intelligence was an unknowable quality which was virtually impossible to replicatec. True Artificial Intelligence is distinguished by the ability to simulate rational processesd. Al is capable of being creative because it can contextualize a response e$.$Two people can have different opinions on the intelligence of a specific agent