Artificial Intelligence: A Modern Approach
3rd Edition
ISBN: 9780136042594
Author: Stuart Russell, Peter Norvig
Publisher: Prentice Hall
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Chapter 2, Problem 6E
a.
Explanation of Solution
Agent
- Yes, more than one agent program can implement a agent function...
b.
Explanation of Solution
Agent program
- Yes,agent function cannot be implemented by any agent program...
c.
Explanation of Solution
Fixed machine architecture
- Yes, each agent program implement exactly one agent function...
d.
Explanation of Solution
Architecture
- There are 2n agent programs...
e.
Explanation of Solution
Architecture
- It depends on the program and the environment.
- If the environment is dynamic, speeding up the machine may mean choosing different actions and/or acting sooner...
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Students have asked these similar questions
a) Explain on Simulated Annealing algorithm behaves at very high temperatures,
and how it behaves at very low temperatures.
(b) Imagine the implementation of Simulated Annealing algorithm in real life. Let's
say, you have a caretaker at your home. Your home has a garden and it has a
fountain with a network of pipes that contains 150 faucets. You informed your
caretaker that you are going for short holiday to Langkawi for 3 days and when
you return you would like the fountain to spray as high as possible. Your
caretaker knows that it is impossible to check all faucets within 3 days to obtain
an optimal setting. You can use Simulated Annealing algorithm to maximize the
height of the fountain, also can assume whether a faucet can be ON or OFF and
measuring the water height. Adding to that, you can make any other
assumptions required for this scenario, explain clearly using Simulated Annealing
algorithm.
Computer Science
You are told that state machine A has one input x, and one output y, both with type {1, 2}, and that it has states {a, b, c, d}. You are told nothing further. Do you have enough information to construct a state machine B that simulates A? If so, give such a state machine, and the simulation relation.
Give the transition diagram for a Turing machine to compute the function
f(x) = x + 3, where x is an integer expressed in unary notation. If you would like to
assume that there is a special symbol such as $ on the left hand side of the tape, that is
fine.
Keep in mind that the Turing machine should end with the read/write head on the first
symbol of the output, and there should be nothing on the tape except the output (and
the $ symbol if you use it).
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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- The state transition diagram for a Turing machine that performs unary increment is shown below. FIGURE 12.6 1/1/R State 1 6/1/R State 2 State diagram for the incrementer Show how this Turing machine will process the input "1111111". You are required to show the configuration of the Turing machine at the beginning of the execution and after each execution step until the Turing machine halts.arrow_forward2. Model a state machine for a chess game using the following description: A chess game consists of alternate moves of Black and White. White moves first (start of the game). The game can end both when it is White's and when it is Black's turn. The moving player can end the game: winning (checkmate), loosing (resign), or with a draw.arrow_forwardConsider the Turing Machine defined as follows: (q0,0,q0,0,R), (q0,1,q1,0,R), (q0,B,q2,B,R), (q1,0,q1,0,R), (q1,1,q0,1,R) and (q1,B,q2,B,R). Describe what this TM does when presented with bit strings defined over the alphabet Σ = {0,1} as input. (Note: B = Blank).arrow_forward
- The language must be in python. The code for parts 1-4 is below. Just do parts 5-7 Neural Network Units Implement a single sigmoid neural network unit with weights of [-1.2, -1.1, 3.3, -2.1] Calculate the outputs for two training examples:Example 1: [0.9, 10.0, 3.1, 1]Example 2: [0.9, 2.1, 3.7, 1] Note that you don't have to explicitly include a threshold or bias since the examples include a last element of 1 which means that the last weight effectively operates as a threshold. Assuming that a sigmoid unit response >0.5 denotes a positive class and <0.5 is negative class, is example 1 positive or negative? is example 2 positive or negative? Create a single ReLU unit and provide the outputs for those examples. Calculate the derivative of the sigmoid with respect to net input for both examples Calculate the derivative of the ReLU with respect to net input for both examples import numpy as np import math def forward(x,w): t = np.dot(x.T,w) t = 1/(1+math.e**(-t))…arrow_forwardSuppose, you are the owner of a bank that operates in a strange way. Customers can lend money from your bank (just like a normal bank) and they can also deposit money in your bank. A register is maintained to track the daily transactions. However, being the strange owner of a strange bank, you have a fascination with finding out whether a portion of your daily transactions (in/out) balance out to zero. For example, suppose your daily transaction register looks like this: 1 Lend 100 2 Deposit 150 3 Lend 400 4 Lend 500 5 Deposit 1000 6 Lend 460 7 Deposit 160 8 Deposit 200 9 Lend 500 10 Depost 100 In this case, there is a portion of the transactions that would balance itself out. (6th, 7th, 8th, and 10th transactions would amount to 0). Your task is to use a genetic algorithm to solve this strange bank problem. Task Breakdown: Model the transaction register in a way suitable for the problem.…arrow_forward3. The state machine in Figure 14.7 has the property that it outputs at least one 1 between any two 0's. Construct a two-state nondeterministic state machine that simulates this one and preserves that property. Give the simulation relation. Are the machines bisimilar? inputs: x: {0,1} outputs: y: {0,1} x=0/1 x=1/0 x=1/1 x = 1/1 x=1/1 30000 x=0/1 x=0/1 x=0/1 Figure 14.7: Machine that outputs at least one 1 between any two 0's.arrow_forward
- How can you use finite automata to model and verify the behavior of a simple vending machine that dispenses different products based on user input and available stock? What kind of automaton would be most appropriate for this scenario, and what would be the language recognized by the automaton?arrow_forwardYour task in this problem is to write a program in the Julia programming language that performs the following:• capture and store a Markov decision process (MDP) at runtime;• given a policy, evaluate the policy, and improve it to get a solution.arrow_forwardi. Design a Turing machine that appends two copies of given strings of 1's to its end. In other words, design a machine that performs computation qow = qwww for any w e {1}* and 9, E F. ii. Show each step of configuration changes of the machine starting from initial configuration: 9611arrow_forward
- Consider the same Simulated Annealing problem as the previous question. Pick the statement that best describes what happens in the next iteration of the Simulated Annealing algorithm. s3, s4, and s5 are equally likely to be the next state s1 is more likely than s2 to be the next state s1 and s2 are equally likely to be the next state s1 is most likely to be the next statearrow_forwardConsider a fully-connected artificial neural network with one hidden layer, i.e., a multilayer perceptron (MLP), which has 5 inputs, 3 neurons in the hidden layer, and 1 output neuron. The relation between the output y and the inputs x = [x1, . . . , x5] is given by y(x) = f (w, φ(x)), where φ(x) = [φ1(x), φ2(x), φ3(x)] 1. Draw the diagram that shows the inputs, nuerons, connections, correspond-ing weight parameters, and activation functions. 2. Explain the relation y(x) = f (w, φ(x)): write the explicit relation, explainthe role of functions f and φ(x), and state examples of functions.arrow_forwardShow how to simulate an arbitrary PDA using a Turing machine. You need not give a formal description of the Turing machine (specifying the states, alphabets, transition function.) A high-level description of the operation of the Turing machine will suffice for this question.arrow_forward
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