Artificial Intelligence: A Modern Approach
3rd Edition
ISBN: 9780136042594
Author: Stuart Russell, Peter Norvig
Publisher: Prentice Hall
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Chapter 2, Problem 9E
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- A reflex agent
program implementing the rational agent function is as follows:
(defun reflex-rational-vacuum-agent (percept)
(destructuring-bind (location status) percept 13
- The utility agent program is
function UTILITY-BASED-AGENT(percept ) returns an action
persistent: state, the agent’s current conception of the world state model , a description of how the next state depends on current stat...
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Chapter 2 Solutions
Artificial Intelligence: A Modern Approach
Ch. 2 - Suppose that the performance measure is concerned...Ch. 2 - Let us examine the rationality of various...Ch. 2 - Prob. 3ECh. 2 - For each of the following activities, give a PEAS...Ch. 2 - Define in your own words the following terms:...Ch. 2 - Prob. 6ECh. 2 - Prob. 7ECh. 2 - Implement a performance-measuring environment...Ch. 2 - Prob. 9ECh. 2 - Prob. 10E
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- In reinforcement learning, we have to predict an action or value of a state/action, this is like a supervised learning task. What makes reinforcement learning more difficult than classification? Select one: a. It is hard to get samples. b. The supervision is delayed c. There is no supervision in any form. d. It is hard to make a state.arrow_forwardConsider the problem of learning the target concept "pairs of people who live in the same house," denoted by the predicate HouseMates(x, y). Below is a positive example of the concept. HouseMates (Joe, Sue) Person(Joe) Person(Sue) Sex(Joe, Male) Sex(Sue, Female) Hair Color (Joe, Black) Haircolor (Sue, Brown) Height ( Joe, Short) Height (Sue, Short) Nationality (Joe, US) Nationality (Sue, US) Mother(Joe, Mary) Mother (Sue, Mary) Age (Joe, 8) Age (Sue, 6) The following domain theory is helpful for acquiring the HouseMates concept: HouseMates(x, y) t InSameFamily(x, y) HouseMates(x, y) t FraternityBrothers (x, y) InSameFamily(x, y) t Married(x, y) InSame Family ( x y) t Youngster (x) A Youngster ( y ) A SameMother ( x, y ) و SameMother(x, y ) t Mother (x, z) A Mother (y, z ) Youngster (x) t Age(x, a ) A LessThan(a, 10) Apply the PROLOG-EBGalgorithm to the task of generalizing from the above instance, using the above domain theory. In particular, (a) Show a hand-trace of the…arrow_forward2. Suppose that an agent is in a 3×3 maze environment like the one shown in Figure 4.19. The agent knows that its initial location is (1,1), that the goal is at (3,3), and that the four actions *Up*, *Down*, *Left*, *Right* have their usual effects unless blocked by a wall. The agent does *not* know where the internal walls are. In any given state, the agent perceives the set of legal actions; it can also tell whether the state is one it has visited before or is a new state. a. Explain how this online search problem can be viewed as an offline search in belief‐state space, where the initial belief state includes all possible environment configurations. How large is the initial belief state? How large is the space of belief states? b. How many distinct percepts are possible in the initial state? c. Describe the first few branches of a contingency plan for this problem. How large (roughly) is the complete plan? Notice that this contingency plan is a solution for *every possible…arrow_forward
- Do you see yourself using email in the not-too-distant future? The path of an email message starts with the sender and concludes with the receiver of the message. Take careful notes on everything you discover. Is there a rationale to the differences, and if so, what are they? Consider the possibility that there exist several models, each of which has a unique level of complexity (or abstraction).arrow_forwardFor problem 2, you should provide two answers for each of the search strategies: the states expanded and the solution. Problem 2 Alice the agent wants to go skiing right after AI class is over. She starts in the lecture hall (the "Start" state below) and wants to make it to Alta (the "Goal" state) as soon as possible. There are several possible paths she can take denoted in the graph below ( refer to image ): The available actions at each state are denoted by arrows with a path cost label above each arrow. For each of the following graph search strategies, figure out the order in which states are expanded as well as the path returned by graph search. When choosing an arbitrary order of state expansions (to break ties), use alphabetical ordering. Remember that in graph search, states are expanded only once. Depth-first search Breadth-first search Uniform cost search A* searcharrow_forwardWrite a Java program to simulate the behaviour of a model-based agent for a vacuum cleaner environment based on the following conditions: The vacuum cleaner can move to one of 4 squares: A, B, C, or D as shown in Table 1. Table 1: vacuum cleaner environment A B C D The vacuum cleaner checks the status of all squares and takes action based on the following order: If all squares are clean, the vacuum cleaner stays in its current location. If the current location is not clean, the vacuum cleaner stays in its current location to clean it up. The vacuum cleaner can only move horizontally or vertically (cannot move diagonally). The vacuum cleaner moves only one square at a time. Horizontal moves have the highest priority over vertical moves. The vacuum cleaner moves to another square only when it needs to be cleaned up. If a diagonal square needs to be cleaned up, the vacuum cleaner moves to its neighbour vertical square first. The vacuum cleaner action is…arrow_forward
- Write a Java program to simulate the behaviour of a model-based agent for a vacuum cleaner environment based on the following conditions: The vacuum cleaner can move to one of 4 squares: A, B, C, or D as shown in Table 1. Table 1: vacuum cleaner environment A B C D The vacuum cleaner checks the status of all squares and takes action based on the following order: If all squares are clean, the vacuum cleaner stays in its current location. If the current location is not clean, the vacuum cleaner stays in its current location to clean it up. The vacuum cleaner can only move horizontally or vertically (cannot move diagonally). The vacuum cleaner moves only one square at a time. Horizontal moves have the highest priority over vertical moves. The vacuum cleaner moves to another square only when it needs to be cleaned up. If a diagonal square needs to be cleaned up, the vacuum cleaner moves to its neighbour vertical square first. The vacuum cleaner action is…arrow_forwardConsider the case when several persons play the wireless phone game. They send a message from the first person until the last one and the message gets distorted. Simulate this process according to your own distortion rules.arrow_forwardWrite a Java program to simulate the behavior of a model-based agent for a vacuum cleaner environment based on the following conditions: The vacuum cleaner can move to one of 4 squares: A, B, C, or D as shown in Table 1. Table 1: vacuum cleaner environment A B C D The vacuum cleaner checks the status of all squares and takes action based on the following order: If all squares are clean, the vacuum cleaner stays in its current location. If the current location is not clean, the vacuum cleaner stays in its current location to clean it up. The vacuum cleaner can only move horizontally or vertically (cannot move diagonally). The vacuum cleaner moves only one square at a time. Horizontal moves have the highest priority over vertical moves. The vacuum cleaner moves to another square only when it needs to be cleaned up. If a diagonal square needs to be cleaned up, the vacuum cleaner moves to its neighbor vertical square first. The vacuum cleaner action is…arrow_forward
- Formulate your own argument (make it creative!) and draw a suitable Euler diagram for it. Justify as well whether it is valid or not. You may emulate the four given arguments below. Example: All Filipinos enjoy singing. Juan is a Filipino. Therefore, Juan enjoys singing. Some physicists are poets. Einstein is a physicist. Therefore, Einstein is a poet. All lions are animals. Some lions have manes.Therefore, some animals have manes. All booms (B) are zooms (Z). All feeps (F) are meeps (M). No boom is a feep. Therefore, no zoom is a meep.arrow_forwardCorrect answer will be upvoted else Multiple Downvoted. Don't submit random answer. Computer science. You have n particular focuses (x1,y1),… ,(xn,yn) on the plane and a non-negative integer boundary k. Each point is a tiny steel ball and k is the draw in force of a ball when it's charged. The draw in power is something very similar for all balls. In one activity, you can choose a ball I to charge it. When charged, all balls with Manhattan distance all things considered k from ball I move to the situation of ball I. Many balls may have a similar facilitate after an activity. All the more officially, for all balls j with the end goal that |xi−xj|+|yi−yj|≤k, we dole out xj:=xi and yj:=yi. An illustration of an activity. Subsequent to charging the ball in the middle, two different balls move to its position. On the right side, the red dab in the middle is the normal situation of those balls. Your errand is to observe the base number of activities to move all balls to a similar…arrow_forwardFive philosophers are sitting at a round table. In the center of the table is a bowl of rice. Between each pair of philosophers is a single chopstick. A philosopher is in one of the three states: thinking, hungry or eating. At various times, a thinking philosopher gets hungry. A hungry philosopher attempts to pick one of the adjacent chopsticks, then the other (not both at the same time). If the philosopher is able to obtain the pair of chopsticks (they are not already in use), then the philosopher eats for a period of time. After eating, the philosopher puts the chopsticks down and returns to thinking. Write a monitor for the dining philosopher’s problem.arrow_forward
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