State space: One general formulation of intelligent action is in terms of state space. A state includes all the necessary information to predict the result of an action and to determine whether it is a target state. The state-space search assumes that, The agent knows the state space well and can observe the state in which it is. The agent has a set of actions proven to have deterministic effects. Several states are target/goal state, the agent wants to enter one of these target state and the agent may identify a target state. A solution is a series of acts that will turn the agent in to a target state from its current state.

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Answer 1

Question

Chapter 3, Problem 27E

Program Plan Intro

State space:

One general formulation of intelligent action is in terms of state space.

A state includes all the necessary information to predict the result of an action and to determine whether it is a target state.

The state-space search assumes that,

The agent knows the state space well and can observe the state in which it is.

The agent has a set of actions proven to have deterministic effects.

Several states are target/goal state, the agent wants to enter one of these target state and the agent may identify a target state.

A solution is a series of acts that will turn the agent in to a target state from its current state.

Program Plan Intro

Branching factor:

The branching factor is the outdegree, the number of children at each node.

If the branching factor is not uniform, it is possible to calculate an average branching factor.

The average branching factor can be determined easily as the number of non-root nodes divided by the number of non-leaf nodes. Where the number of root node is determined by as the size of the tree, minus one.

Program Plan Intro

Admissible heuristic:

A heuristic h(s) is admissible, if for every node n, h(s)≤h(s) is the true cost to reach the goal state from n

An admissible heuristic never over estimates the cost to reach the goal. That is optimistic. Sensorless search problem defines by four items. That are given below,

1. Initial state

2. Description of action: successor function h(s) = set of action-state pairs

3. Goal test, can be

Explicit

Implicit

4 Path cost. It reflects the performance measure.

An admissible heuristic can be obtained by taking maximum of h(s). Since any sequences of actions that solve all states would solve each state, this heuristic is admissible.

Program Plan Intro

Admissible heuristic:

A heuristic h(s) is admissible, if for every node n, h(s)≤h(s) is the true cost to reach the goal state from n

An admissible heuristic never over estimates the cost to reach the goal. That is optimistic. Sensorless search problem defines by four items. That are given below,

4. Initial state

5. Description of action: successor function h(s) = set of action-state pairs

6. Goal test, can be

Explicit

Implicit

5 Path cost. It reflects the performance measure.

An admissible heuristic can be obtained by taking maximum of h(s). Since any sequences of actions that solve all states would solve each state, this heuristic is admissible.

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There is an upcoming football tournament, and the n participating teams are labelled from 1 to n. Each pair of teams will play against each other exactly once. Thus, a total of [n(n-1)/2] matches will be held, and each team will compete in n − 1 of these matches. There are only two possible outcomes of a match: 1. The match ends in a draw, in which case both teams will get 1 point. 2. One team wins the match, in which case the winning team gets 3 points and the losing team gets 0 points. Design an algorithm which runs in O(n2 ) time and provides a list of results in all [n(n-1)/2] matches which: (a) ensures that all n teams finish with the same points total, and (b) includes the fewest drawn matches among all lists satisfying (a). Do not write the code, give steps and methods. Explain the steps of algorithm, and the logic behind these steps in plain English list of results mean Any combination of wins, losses and draws. You may wish to view this as a mapping from the set of distinct…

In a tournament, there are n participating teams are labelled from 1 to n. Each pair of teams will play against each other exactly once. Thus, a total of [n(n-1)/2] matches will be held, and each team will compete in n − 1 of these matches. There are only two possible outcomes of a match: 1. The match ends in a draw, in which case both teams will get 1 point. 2. One team wins the match, in which case the winning team gets 3 points and the losing team gets 0 points. Design an algorithm which runs in O(n2 ) time and provides a list of results in all [n(n-1)/2] matches which: (a) ensures that all n teams finish with the same points total, and (b) includes the fewest drawn matches among all lists satisfying (a). Do not write the code, give steps and methods. Explain the steps of algorithm, and the logic behind these steps in plain English

In a tournament, there are n participating teams are labelled from 1 to n. Each pair of teams will play against each other exactly once. Thus, a total of [n(n-1)/2] matches will be held, and each team will compete in n − 1 of these matches. There are only two possible outcomes of a match: 1. The match ends in a draw, in which case both teams will get 1 point. 2. One team wins the match, in which case the winning team gets 3 points and the losing team gets 0 points. Design an algorithm which runs in O(n2 ) time and provides a list of results in all [n(n-1)/2] matches which: (a) ensures that all n teams finish with the same points total, and (b) includes the fewest drawn matches among all lists satisfying (a). Do not write the code, give steps and methods. Explain the steps of algorithm, and the logic behind these steps in plain English. PLease give the total time complexity.

Answer 2

Question

Chapter 3, Problem 27E

Program Plan Intro

State space:

One general formulation of intelligent action is in terms of state space.

A state includes all the necessary information to predict the result of an action and to determine whether it is a target state.

The state-space search assumes that,

The agent knows the state space well and can observe the state in which it is.

The agent has a set of actions proven to have deterministic effects.

Several states are target/goal state, the agent wants to enter one of these target state and the agent may identify a target state.

A solution is a series of acts that will turn the agent in to a target state from its current state.

Program Plan Intro

Branching factor:

The branching factor is the outdegree, the number of children at each node.

If the branching factor is not uniform, it is possible to calculate an average branching factor.

The average branching factor can be determined easily as the number of non-root nodes divided by the number of non-leaf nodes. Where the number of root node is determined by as the size of the tree, minus one.

Program Plan Intro

Admissible heuristic:

A heuristic h(s) is admissible, if for every node n, h(s)≤h(s) is the true cost to reach the goal state from n

An admissible heuristic never over estimates the cost to reach the goal. That is optimistic. Sensorless search problem defines by four items. That are given below,

1. Initial state

2. Description of action: successor function h(s) = set of action-state pairs

3. Goal test, can be

Explicit

Implicit

4 Path cost. It reflects the performance measure.

An admissible heuristic can be obtained by taking maximum of h(s). Since any sequences of actions that solve all states would solve each state, this heuristic is admissible.

Program Plan Intro

Admissible heuristic:

A heuristic h(s) is admissible, if for every node n, h(s)≤h(s) is the true cost to reach the goal state from n

An admissible heuristic never over estimates the cost to reach the goal. That is optimistic. Sensorless search problem defines by four items. That are given below,

4. Initial state

5. Description of action: successor function h(s) = set of action-state pairs

6. Goal test, can be

Explicit

Implicit

5 Path cost. It reflects the performance measure.

An admissible heuristic can be obtained by taking maximum of h(s). Since any sequences of actions that solve all states would solve each state, this heuristic is admissible.

Expert Solution & Answer

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Answer 3

Question

Chapter 3, Problem 27E

Program Plan Intro

State space:

One general formulation of intelligent action is in terms of state space.

A state includes all the necessary information to predict the result of an action and to determine whether it is a target state.

The state-space search assumes that,

The agent knows the state space well and can observe the state in which it is.

The agent has a set of actions proven to have deterministic effects.

Several states are target/goal state, the agent wants to enter one of these target state and the agent may identify a target state.

A solution is a series of acts that will turn the agent in to a target state from its current state.

Program Plan Intro

Branching factor:

The branching factor is the outdegree, the number of children at each node.

If the branching factor is not uniform, it is possible to calculate an average branching factor.

The average branching factor can be determined easily as the number of non-root nodes divided by the number of non-leaf nodes. Where the number of root node is determined by as the size of the tree, minus one.

Program Plan Intro

Admissible heuristic:

A heuristic h(s) is admissible, if for every node n, h(s)≤h(s) is the true cost to reach the goal state from n

An admissible heuristic never over estimates the cost to reach the goal. That is optimistic. Sensorless search problem defines by four items. That are given below,

1. Initial state

2. Description of action: successor function h(s) = set of action-state pairs

3. Goal test, can be

Explicit

Implicit

4 Path cost. It reflects the performance measure.

An admissible heuristic can be obtained by taking maximum of h(s). Since any sequences of actions that solve all states would solve each state, this heuristic is admissible.

Program Plan Intro

Admissible heuristic:

A heuristic h(s) is admissible, if for every node n, h(s)≤h(s) is the true cost to reach the goal state from n

An admissible heuristic never over estimates the cost to reach the goal. That is optimistic. Sensorless search problem defines by four items. That are given below,

4. Initial state

5. Description of action: successor function h(s) = set of action-state pairs

6. Goal test, can be

Explicit

Implicit

5 Path cost. It reflects the performance measure.

An admissible heuristic can be obtained by taking maximum of h(s). Since any sequences of actions that solve all states would solve each state, this heuristic is admissible.

Expert Solution & Answer

Want to see the full answer?

Check out a sample textbook solution

See solution

Answer 4

Question

Chapter 3, Problem 27E

Program Plan Intro

State space:

One general formulation of intelligent action is in terms of state space.

A state includes all the necessary information to predict the result of an action and to determine whether it is a target state.

The state-space search assumes that,

The agent knows the state space well and can observe the state in which it is.

The agent has a set of actions proven to have deterministic effects.

Several states are target/goal state, the agent wants to enter one of these target state and the agent may identify a target state.

A solution is a series of acts that will turn the agent in to a target state from its current state.

Program Plan Intro

Branching factor:

The branching factor is the outdegree, the number of children at each node.

If the branching factor is not uniform, it is possible to calculate an average branching factor.

The average branching factor can be determined easily as the number of non-root nodes divided by the number of non-leaf nodes. Where the number of root node is determined by as the size of the tree, minus one.

Program Plan Intro

Admissible heuristic:

A heuristic h(s) is admissible, if for every node n, h(s)≤h(s) is the true cost to reach the goal state from n

An admissible heuristic never over estimates the cost to reach the goal. That is optimistic. Sensorless search problem defines by four items. That are given below,

1. Initial state

2. Description of action: successor function h(s) = set of action-state pairs

3. Goal test, can be

Explicit

Implicit

4 Path cost. It reflects the performance measure.

An admissible heuristic can be obtained by taking maximum of h(s). Since any sequences of actions that solve all states would solve each state, this heuristic is admissible.

Program Plan Intro

Admissible heuristic:

A heuristic h(s) is admissible, if for every node n, h(s)≤h(s) is the true cost to reach the goal state from n

An admissible heuristic never over estimates the cost to reach the goal. That is optimistic. Sensorless search problem defines by four items. That are given below,

4. Initial state

5. Description of action: successor function h(s) = set of action-state pairs

6. Goal test, can be

Explicit

Implicit

5 Path cost. It reflects the performance measure.

An admissible heuristic can be obtained by taking maximum of h(s). Since any sequences of actions that solve all states would solve each state, this heuristic is admissible.

Expert Solution & Answer

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Check out a sample textbook solution

See solution

Answer 5

Chapter 3, Problem 27E

Program Plan Intro

State space:

One general formulation of intelligent action is in terms of state space.

A state includes all the necessary information to predict the result of an action and to determine whether it is a target state.

The state-space search assumes that,

The agent knows the state space well and can observe the state in which it is.

The agent has a set of actions proven to have deterministic effects.

Several states are target/goal state, the agent wants to enter one of these target state and the agent may identify a target state.

A solution is a series of acts that will turn the agent in to a target state from its current state.

Program Plan Intro

Branching factor:

The branching factor is the outdegree, the number of children at each node.

If the branching factor is not uniform, it is possible to calculate an average branching factor.

The average branching factor can be determined easily as the number of non-root nodes divided by the number of non-leaf nodes. Where the number of root node is determined by as the size of the tree, minus one.

Program Plan Intro

Admissible heuristic:

A heuristic h(s) is admissible, if for every node n, h(s)≤h(s) is the true cost to reach the goal state from n

An admissible heuristic never over estimates the cost to reach the goal. That is optimistic. Sensorless search problem defines by four items. That are given below,

1. Initial state

2. Description of action: successor function h(s) = set of action-state pairs

3. Goal test, can be

Explicit

Implicit

4 Path cost. It reflects the performance measure.

An admissible heuristic can be obtained by taking maximum of h(s). Since any sequences of actions that solve all states would solve each state, this heuristic is admissible.

Program Plan Intro

Admissible heuristic:

A heuristic h(s) is admissible, if for every node n, h(s)≤h(s) is the true cost to reach the goal state from n

An admissible heuristic never over estimates the cost to reach the goal. That is optimistic. Sensorless search problem defines by four items. That are given below,

4. Initial state

5. Description of action: successor function h(s) = set of action-state pairs

6. Goal test, can be

Explicit

Implicit

5 Path cost. It reflects the performance measure.

An admissible heuristic can be obtained by taking maximum of h(s). Since any sequences of actions that solve all states would solve each state, this heuristic is admissible.

Answer 6

Chapter 3, Problem 27E

Program Plan Intro

State space:

One general formulation of intelligent action is in terms of state space.

A state includes all the necessary information to predict the result of an action and to determine whether it is a target state.

The state-space search assumes that,

The agent knows the state space well and can observe the state in which it is.

The agent has a set of actions proven to have deterministic effects.

Several states are target/goal state, the agent wants to enter one of these target state and the agent may identify a target state.

A solution is a series of acts that will turn the agent in to a target state from its current state.

Answer 7

Chapter 3, Problem 27E

Program Plan Intro

State space:

One general formulation of intelligent action is in terms of state space.

A state includes all the necessary information to predict the result of an action and to determine whether it is a target state.

The state-space search assumes that,

The agent knows the state space well and can observe the state in which it is.

The agent has a set of actions proven to have deterministic effects.

Several states are target/goal state, the agent wants to enter one of these target state and the agent may identify a target state.

A solution is a series of acts that will turn the agent in to a target state from its current state.

Answer 8

Program Plan Intro

Branching factor:

The branching factor is the outdegree, the number of children at each node.

If the branching factor is not uniform, it is possible to calculate an average branching factor.

The average branching factor can be determined easily as the number of non-root nodes divided by the number of non-leaf nodes. Where the number of root node is determined by as the size of the tree, minus one.

Answer 9

Program Plan Intro

Branching factor:

The branching factor is the outdegree, the number of children at each node.

If the branching factor is not uniform, it is possible to calculate an average branching factor.

The average branching factor can be determined easily as the number of non-root nodes divided by the number of non-leaf nodes. Where the number of root node is determined by as the size of the tree, minus one.

Answer 10

Program Plan Intro

Admissible heuristic:

A heuristic h(s) is admissible, if for every node n, h(s)≤h(s) is the true cost to reach the goal state from n

An admissible heuristic never over estimates the cost to reach the goal. That is optimistic. Sensorless search problem defines by four items. That are given below,

1. Initial state

2. Description of action: successor function h(s) = set of action-state pairs

3. Goal test, can be

Explicit

Implicit

4 Path cost. It reflects the performance measure.

An admissible heuristic can be obtained by taking maximum of h(s). Since any sequences of actions that solve all states would solve each state, this heuristic is admissible.

Answer 11

Program Plan Intro

Admissible heuristic:

A heuristic h(s) is admissible, if for every node n, h(s)≤h(s) is the true cost to reach the goal state from n

An admissible heuristic never over estimates the cost to reach the goal. That is optimistic. Sensorless search problem defines by four items. That are given below,

1. Initial state

2. Description of action: successor function h(s) = set of action-state pairs

3. Goal test, can be

Explicit

Implicit

4 Path cost. It reflects the performance measure.

An admissible heuristic can be obtained by taking maximum of h(s). Since any sequences of actions that solve all states would solve each state, this heuristic is admissible.

Answer 12

Program Plan Intro

Admissible heuristic:

A heuristic h(s) is admissible, if for every node n, h(s)≤h(s) is the true cost to reach the goal state from n

An admissible heuristic never over estimates the cost to reach the goal. That is optimistic. Sensorless search problem defines by four items. That are given below,

4. Initial state

5. Description of action: successor function h(s) = set of action-state pairs

6. Goal test, can be

Explicit

Implicit

5 Path cost. It reflects the performance measure.

An admissible heuristic can be obtained by taking maximum of h(s). Since any sequences of actions that solve all states would solve each state, this heuristic is admissible.

Answer 13

Program Plan Intro

Admissible heuristic:

A heuristic h(s) is admissible, if for every node n, h(s)≤h(s) is the true cost to reach the goal state from n

An admissible heuristic never over estimates the cost to reach the goal. That is optimistic. Sensorless search problem defines by four items. That are given below,

4. Initial state

5. Description of action: successor function h(s) = set of action-state pairs

6. Goal test, can be

Explicit

Implicit

5 Path cost. It reflects the performance measure.

An admissible heuristic can be obtained by taking maximum of h(s). Since any sequences of actions that solve all states would solve each state, this heuristic is admissible.

Answer 14

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Answer 15

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Answer 16

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Answer 17

Ch. 3 - Explain why problem formulation must follow goal...Ch. 3 - Prob. 2E Ch. 3 - Prob. 3E Ch. 3 - Prob. 4E Ch. 3 - Prob. 5E Ch. 3 - Prob. 6E Ch. 3 - Prob. 8E Ch. 3 - Prob. 9E Ch. 3 - Prob. 10E Ch. 3 - Prob. 11E

Solution Summary: The author explains the state-space search, which assumes that the agent knows state space well and can observe it. The branching factor is the number of children at each node.

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