Search algorithms assume that action costs are strictly positive (>0). Suppose you have a search problem...

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Search algorithms assume that action costs are strictly positive (>0). Suppose you have a search problem for which you want some actions to have a negative or a 0 cost. Answer the following questions briefly but precisely: Q1: What would be an example of a problem where negative costs would be useful? Q2: What is the effect of arcs with negative or zero costs on the behavior of search algorithms that use the cost of the actions in the search process? Be precise and consider cases where the state space is a tree and cases where it is a graph with or without cycles. Q3: Does it make any difference if there is a lower bound on the value of the negative costs (i.e. a cost is greater or equal to some negative constant)? Search algorithms assume that action costs are strictly positive (>0). Suppose you have a search problem for which you want some actions to have a negative or a 0 cost. Answer the following questions briefly but precisely: Q1: What would be an example of a problem where negative costs would be useful? Q2: What is the effect of arcs with negative or zero costs on the behavior of search algorithms that use the cost of the actions in the search process? Be precise and consider cases where the state space is a tree and cases where it is a graph with or without cycles. Q3: Does it make any difference if there is a lower bound on the value of the negative costs (i.e. a cost is greater or equal to some negative constant)?

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The text in the image outlines queries about the use of negative or zerocost actions in search algorithms Here is a detailed explanation for each ques... View the full answer