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_site/advanced-search-exercises/ex_11/index.html

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<div id="hiddden">
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Consider the sensorless version of the
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erratic vacuum world. Draw the belief-state space reachable from the
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initial belief state $\{ 1,3,5,7 \}$, and explain why the problem
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is unsolvable.
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_site/advanced-search-exercises/ex_13/index.html

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<div id="hiddden">
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Suppose that an agent is in a $3 \times 3$
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maze environment like the one shown in
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Figure <a href="#">maze-3x3-figure</a>. The agent knows that its
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initial location is (1,1), that the goal is at (3,3), and that the
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actions *Up*, *Down*, *Left*, *Right* have their usual
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effects unless blocked by a wall. The agent does *not* know
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where the internal walls are. In any given state, the agent perceives
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the set of legal actions; it can also tell whether the state is one it
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has visited before.<br />
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1. Explain how this online search problem can be viewed as an offline
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search in belief-state space, where the initial belief state
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includes all possible environment configurations. How large is the
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initial belief state? How large is the space of belief states?<br />
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2. How many distinct percepts are possible in the initial state?<br />
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3. Describe the first few branches of a contingency plan for this
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problem. How large (roughly) is the complete plan?<br />
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Notice that this contingency plan is a solution for *every
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possible environment* fitting the given description. Therefore,
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interleaving of search and execution is not strictly necessary even in
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unknown environments.
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_site/advanced-search-exercises/ex_3/index.html

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<div id="hiddden">
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In this exercise, we explore the use of local search methods to solve
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TSPs of the type defined in Exercise <a href="#">tsp-mst-exercise</a><br />
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1. Implement and test a hill-climbing method to solve TSPs. Compare the
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results with optimal solutions obtained from the A* algorithm with
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the MST heuristic (Exercise <a href="#">tsp-mst-exercise</a>)<br />
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2. Repeat part (a) using a genetic algorithm instead of hill climbing.
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You may want to consult @Larranaga+al:1999 for some suggestions for representations.
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_site/complex-decisions-exercises/ex_8/index.html

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<div id="hiddden">
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Equation (<a href="#">vi-contraction-equation</a>) on
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page <a href="#">vi-contraction-equation</a> states that the Bellman operator is a contraction.<br />
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1. Show that, for any functions $f$ and $g$,
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$$|\max_a f(a) - \max_a g(a)| \leq \max_a |f(a) - g(a)|\ .$$<br />
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2. Write out an expression for $$|(B\,U_i - B\,U'_i)(s)|$$ and then apply
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the result from (1) to complete the proof that the Bellman operator
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is a contraction.<br />
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_site/intro-exercises/ex_17/index.html

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<p>“Surely animals, humans, and computers cannot be intelligent—they can do
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“Surely animals, humans, and computers cannot be intelligent—they can do
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only what their constituent atoms are told to do by the laws of
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physics.” Is the latter statement true, and does it imply the former?</p>
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physics.” Is the latter statement true, and does it imply the former?
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_site/kr-exercises/ex_22/index.html

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<div id="hiddden">
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(Adapted from @Fagin+al:1995.) Consider a game played
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with a deck of just 8 cards, 4 aces and 4 kings. The three players,
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Alice, Bob, and Carlos, are dealt two cards each. Without looking at
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them, they place the cards on their foreheads so that the other players
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can see them. Then the players take turns either announcing that they
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know what cards are on their own forehead, thereby winning the game, or
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saying “I don’t know.” Everyone knows the players are truthful and are
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perfect at reasoning about beliefs.<br />
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1. Game 1. Alice and Bob have both said “I don’t know.” Carlos sees
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that Alice has two aces (A-A) and Bob has two kings (K-K). What
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should Carlos say? (<i>Hint</i>: consider all three possible
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cases for Carlos: A-A, K-K, A-K.)<br />
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2. Describe each step of Game 1 using the notation of modal logic.<br />
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3. Game 2. Carlos, Alice, and Bob all said “I don’t know” on their
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first turn. Alice holds K-K and Bob holds A-K. What should Carlos
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say on his second turn?<br />
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4. Game 3. Alice, Carlos, and Bob all say “I don’t know” on their first
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turn, as does Alice on her second turn. Alice and Bob both hold A-K.
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What should Carlos say?<br />
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5. Prove that there will always be a winner to this game.<br />
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_site/logical-inference-exercises/ex_11/index.html

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<div id="hiddden">
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Suppose you are given the following axioms:<br />
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1. $0 \leq 3$.<br />
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2. $7 \leq 9$.<br />
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3. ${\forall\,x\;\;} \; \; x \leq x$.<br />
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4. ${\forall\,x\;\;} \; \; x \leq x+0$.<br />
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5. ${\forall\,x\;\;} \; \; x+0 \leq x$.<br />
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6. ${\forall\,x,y\;\;} \; \; x+y \leq y+x$.<br />
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7. ${\forall\,w,x,y,z\;\;} \; \; w \leq y$ $\wedge$ $x \leq z$ ${\:\;{\Rightarrow}\:\;}$ $w+x \leq y+z$.<br />
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8. ${\forall\,x,y,z\;\;} \; \; x \leq y \wedge y \leq z \: {\:\;{\Rightarrow}\:\;}\: x \leq z$ <br />
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<br />
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1. Give a backward-chaining proof of the sentence $7 \leq 3+9$. (Be
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sure, of course, to use only the axioms given here, not anything
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else you may know about arithmetic.) Show only the steps that leads
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to success, not the irrelevant steps.<br />
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2. Give a forward-chaining proof of the sentence $7 \leq 3+9$. Again,
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show only the steps that lead to success.<br />
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_site/logical-inference-exercises/ex_13/index.html

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<div id="hiddden">
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A popular children’s riddle is “Brothers and sisters have I none, but
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that man’s father is my father’s son.” Use the rules of the family
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domain (Section <a href="#">kinship-domain-section</a> on
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page <a href="#">kinship-domain-section</a> to show who that man is. You may apply any of the
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inference methods described in this chapter. Why do you think that this
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riddle is difficult?
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_site/search-exercises/ex_10/index.html

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<div id="hiddden">
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On page <a href="#">non-negative-g</a>, we said that we would not consider problems
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with negative path costs. In this exercise, we explore this decision in
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more depth.<br />
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1. Suppose that actions can have arbitrarily large negative costs;
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explain why this possibility would force any optimal algorithm to
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explore the entire state space.<br />
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2. Does it help if we insist that step costs must be greater than or
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equal to some negative constant $c$? Consider both trees and graphs.<br />
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3. Suppose that a set of actions forms a loop in the state space such
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that executing the set in some order results in no net change to
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the state. If all of these actions have negative cost, what does
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this imply about the optimal behavior for an agent in such an
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environment?<br />
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4. One can easily imagine actions with high negative cost, even in
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domains such as route finding. For example, some stretches of road
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might have such beautiful scenery as to far outweigh the normal
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costs in terms of time and fuel. Explain, in precise terms, within
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the context of state-space search, why humans do not drive around
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scenic loops indefinitely, and explain how to define the state space
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and actions for route finding so that artificial agents can also
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avoid looping.<br />
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5. Can you think of a real domain in which step costs are such as to
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cause looping?<br />
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