• sweep: sweep the floor the robot is in.

(a) Give the STRIPS representation for dust. [Hint: because STRIPS cannot represent conditional effects, you may need to use two separate actions that depend on the robot’s location.]

(b) Give the feature-based representation for lr_dusty

(c) Suppose that the initial state is that the robot is in the garage, both rooms are dusty but have clean floors and the goal is to have both rooms not dusty. Draw the first two levels (with two actions, so the root has children and grandchildren) of a forward planner with multiple-path pruning, showing the actions (but you do not have to show the states). Show explicitly what nodes are pruned through multiple-path pruning.

(d) Pick two of the states at the second level (after two actions) and show what is true in those states

(e) Suppose that the initial state is that the robot is in the garage, both rooms are dusty but have clean floors and the goal is to have both rooms not dusty. Draw the first two levels (with two actions, so the root has children and grandchildren) of a regression planner showing the actions but you do not have to show what the nodes represent.

(f) Pick two of the nodes at the second level (after two actions) and show what the subgoal is at those nodes.
(g) Draw the CSP for a planning horizon of two. Describe each constraint in English by specifying which values are (in)consistent.
(h) In designing the actions, the above description made one choice of what to include as preconditions of the actions. Consider the choices of whether to have the room is dusty as a precondition for cleaning the room, and whether to have the floor is dirty as a precondition for sweeping. Do these choices make a difference to (i) the shortest plan, (ii) the size of the search space for a forward planner or (iii) the size of the search space for a regression planner?