Consider the following vacuum-cleaning world which has 3 squares we assume the following .the vacuum-cleaning agent knows the configuration of the 3 squares, but does not know which square it is in initially. the initial dirt distribution is not known either .a clean square remains clean and a dirty square remains dirty unless the agent cleans it up. the agent has two sensors: loc(x) and status(x). loc(x) returns the identity ("a" or "b" or "c") of the square x that the agent is located, and status(x) returns either "dirty" or "clean for the square x. assume that the sensors are 100% reliable th actions available for the agent are: left, right, suck, noop. each action takes place in the actions are perfectly reliable - perform "suck" in dirty square will change it to become the agent will be penalized by -1 point for each movement left, right, suck. the agent gets · for a time horizon t (say t = 100) steps, the agent is penalized by-2 points per dirty square one time "step" clean, and moving left when in square c will get the agent to square b +10 points reward for each dirty square cleaned. per time step. (if a square is dirty at the "start" of time step t and the agent performs "suck" at this time step, the square becomes "clean" at the "end" of step t. thus for time step t for this particular square, no penality should be applied to the agent) the agent's performance is measured by the total number of points (positive or negative) over t- 100 time steps. (a) design a simple reflex agent (without states) for this problem - provide pseudo-code for the agent and define the "condition-action" rules. can such an agent be perfectly rational (i. e., maximizing the expected performance measure) for any initial agent location and dirt distribu- tion? explain your answer (b) what about a reflex agent with states (i. e., an agent which has an internal state representation of the world environment)? can such an agent be perfectly rational under the current assump- tions? design such an agent (pseudo-code, rules, or look-up table, etc.) (c) now assume that the agent's dirt sensor is more powerful which provides complete information about dirty/clean status of every square in the environment. can a simple reflex agent be per fectly rational now? and if so, design such an agent (pseudo-code, rules, or look-up table, etc