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+<div id="hiddden">
+
+The goals we have considered so far all ask the planner to make the
+world satisfy the goal at just one time step. Not all goals can be
+expressed this way: you do not achieve the goal of suspending a
+chandelier above the ground by throwing it in the air. More seriously,
+you wouldn’t want your spacecraft life-support system to supply oxygen
+one day but not the next. A <i>maintenance goal</i> is achieved
+when the agent’s plan causes a condition to hold continuously from a
+given state onward. Describe how to extend the formalism of this chapter
+to support maintenance goals.
+</div>
 
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+<div id="hiddden">
+
+In the blocks world we were forced to introduce two action schemas,
+${Move}$ and ${MoveToTable}$, in order to maintain the ${Clear}$
+predicate properly. Show how conditional effects can be used to
+represent both of these cases with a single action.
+</div>
 
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+<div id="hiddden">
+
+Conditional effects were illustrated for the
+${Suck}$ action in the vacuum world—which square becomes clean depends
+on which square the robot is in. Can you think of a new set of
+propositional variables to define states of the vacuum world, such that
+${Suck}$ has an <i>unconditional</i> description? Write out
+the descriptions of ${Suck}$, ${Left}$, and ${Right}$, using your
+propositions, and demonstrate that they suffice to describe all possible
+states of the world.
+</div>
 
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+<div id="hiddden">
+
+Find a suitably dirty carpet, free of obstacles, and vacuum it. Draw the
+path taken by the vacuum cleaner as accurately as you can. Explain it,
+with reference to the forms of planning discussed in this chapter.
+</div>
 
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+<div id="hiddden">
+
+The following quotes are from the backs of shampoo bottles. Identify
+each as an unconditional, conditional, or execution-monitoring plan. (a)
+“Lather. Rinse. Repeat.” (b) “Apply shampoo to scalp and let it remain
+for several minutes. Rinse and repeat if necessary.” (c) “See a doctor
+if problems persist.”
+</div>
 
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+<div id="hiddden">
+
+Consider the following problem: A patient arrives at the doctor’s office
+with symptoms that could have been caused either by dehydration or by
+disease $D$ (but not both). There are two possible actions: ${Drink}$,
+which unconditionally cures dehydration, and ${Medicate}$, which cures
+disease $D$ but has an undesirable side effect if taken when the patient
+is dehydrated. Write the problem description, and diagram a sensorless
+plan that solves the problem, enumerating all relevant possible worlds.
+</div>
 
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+<div id="hiddden">
+
+To the medication problem in the previous exercise, add a ${Test}$
+action that has the conditional effect ${CultureGrowth}$ when
+${Disease}$ is true and in any case has the perceptual effect
+${Known}({CultureGrowth})$. Diagram a conditional plan that solves
+the problem and minimizes the use of the ${Medicate}$ action.
+</div>
 
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+<div id="hiddden">
+
+You have a number of trucks with which to deliver a set of packages.
+Each package starts at some location on a grid map, and has a
+destination somewhere else. Each truck is directly controlled by moving
+forward and turning. Construct a hierarchy of high-level actions for
+this problem. What knowledge about the solution does your hierarchy
+encode?
+</div>
 
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+<div id="hiddden">
+
+Suppose that a high-level action has exactly one
+implementation as a sequence of primitive actions. Give an algorithm for
+computing its preconditions and effects, given the complete refinement
+hierarchy and schemas for the primitive actions.
+</div>
 
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+<div id="hiddden">
+
+Suppose that the optimistic reachable set of a high-level plan is a
+superset of the goal set; can anything be concluded about whether the
+plan achieves the goal? What if the pessimistic reachable set doesn’t
+intersect the goal set? Explain.
+</div>
 
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+<div id="hiddden">[Exercise 11.5 \[HLA-progression-exercise\]](ex_5/)
+
+Write an algorithm that takes an initial
+state (specified by a set of propositional literals) and a sequence of
+HLAs (each defined by preconditions and angelic specifications of
+optimistic and pessimistic reachable sets) and computes optimistic and
+pessimistic descriptions of the reachable set of the sequence.
+</div>
 
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