Artificial Intelligence Foundations Of Computational Agents 2nd Edition David L. Poole, Alan K. Mackworth - Solutions

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Trace the good-dog problem of Example
Write a backtrack algorithm for and/or graphs.
Choose and justify a choice of breadth- or depth-first search for examples of Exercise
Determine whether goal-driven or data-driven search would be preferable for solving each of the following problems. Justify your answer.a. Diagnosing mechanical problems in an automobile.b. C.d. e.f. You have met a person who claims to be your distant cousin, with a common ancestor named John Doe.
27. Begin from state A. Keep track of the successive values of NSL, SL, CS, etc.
"Hand run" the backtrack algorithm on the graph in Figure
Discuss the advan- tages of breadth-first and depth-first for searching this space?
2). Let the nodes represent states of the world; e.g., the farmer and the goat are on the west bank and the wolf and cabbage on the east?
1 and
3 (see Figures
Give the graph representation for the farmer, wolf, goat, and cabbage problem of Section
Is there such a path in the Knigsberg map?
A Hamiltonian path is a path that uses every node of the graph exactly once. What condi- tions are necessary for such a path to exist?
How can an interpreter be designed to most effectively utilize a representation language?
How can the interpreter most effectively reduce search complexity?
What is the complexity of the search process in terms of time usage? Space usage?
When a solution is found, is it guaranteed to be optimal?
Will the problem solver always terminate, or can it become caught in an infinite loop?
List and discuss two potentially negative effects on society of the development of artificial intelligence techniques.?
Discuss your thoughts on the mind-body problem and its importance for a theory of artificial intelligence.
Much traditional Western thought has dwelt on the mind-body relationship. Are the mind and body:a. b. distinct entities somehow interacting, or is mind an expression of "physical processes," or C. is body just an illusion of the rational mind?
Answers that are neither exact nor optimal, but are in some sense "sufficient." This is a result of the essential reliance on heuristic problem-solving methods in situations where optimal or exact results are either too expensive or not possible.?
An attempt to deal with issues of semantic meaning as well as syntactic form.?
Reasoning about the significant qualitative features of a situation.?
A concern with problem solving using inexact, missing, or poorly defined information and the use of representational formalisms that enable the programmer to compensate for these problems. ?
A focus on problems that do not respond to algorithmic solutions. This underlies the reliance on heuristic search as an AI problem-solving technique.?
The use of computers to do symbolic reasoning, pattern recognition, learning, or some other form of inference.?
Little learning from experience. Current expert systems are handcrafted; once the system is completed, its performance will not improve without further attention from its programmers. This leads to severe doubts about the intelligence of such systems.?
Difficulties in verification. Though the correctness of any large computer system is difficult to prove, expert systems are particularly difficult to verify. This is a serious problem, as expert systems technology is being applied to critical applications such as air traffic control, nuclear
Inability to provide deep explanations. Because expert systems lack deep knowledge of their problem domains, their explanations are generally restricted to a description of the steps they took in finding a solution. They cannot tell "why" a certain approach was taken.?
Lack of robustness and flexibility. If humans are presented with a problem instance that they cannot solve immediately, they can generally return to an examination of first principles and come up with some strategy for attacking the problem. Expert systems generally lack this ability.?
Difficulty in capturing "deep" knowledge of the problem domain. MYCIN, for example, lacks any real knowledge of human physiology. It does not know what blood does or the function of the spinal cord. Folklore has it that once, when selecting a drug for treatment of meningitis, MYCIN asked whether
3.6 that allows complex sentences, such as, sentence sentence ?? sentence.
Add grammar rules to Example
3.6.
Add rules for (multiple) prepositional phrases to Example
3.6.
Add rules defining adjectives and adverbs to the grammar of Example
3.5 for the case of an individual with four dependents, $18,000 in the bank, and a steady income of $25,000 per year. Based on a comparison of this problem and the example in the text, suggest a generally "best" strategy for solving the problem.
Trace a data-driven execution of the financial advisor of Example
Give another example of an and/or graph search problem and develop part of the search space.
3.4 in a data-driven fashion.
Trace the good-dog problem of Example
13. Add rules for (multiple) prepositional phrases to Example 3.3.6.
Choose and justify a choice of breadth- or depth-first search for examples of Exercise
Determine whether goal-driven or data-driven search would be preferable for solving each of the following problems. Justify your answer.a. Diagnosing mechanical problems in an automobile.b. C.d. e.f. You have met a person who claims to be your distant cousin, with a common ancestor named John Doe.
27. Begin from state A. Keep track of the successive values of NSL, SL, CS, etc.
"Hand run" the backtrack algorithm on the graph in Figure
Discuss the advan- tages of breadth-first and depth-first for searching this space?
2). Let the nodes represent states of the world; e.g., the farmer and the goat are on the west bank and the wolf and cabbage on the east?
1 and
3 (see Figures
Give the graph representation for the farmer, wolf, goat, and cabbage problem of Section
Is there such a path in the Knigsberg map?
A Hamiltonian path is a path that uses every node of the graph exactly once. What condi- tions are necessary for such a path to exist?
How can an interpreter be designed to most effectively utilize a representation language?
How can the interpreter most effectively reduce search complexity?
What is the complexity of the search process in terms of time usage? Space usage?
When a solution is found, is it guaranteed to be optimal?
Will the problem solver always terminate, or can it become caught in an infinite loop?
List and discuss two potentially negative effects on society of the development of artificial intelligence techniques.?
Discuss your thoughts on the mind-body problem and its importance for a theory of artificial intelligence.
Much traditional Western thought has dwelt on the mind-body relationship. Are the mind and body:a. b. distinct entities somehow interacting, or is mind an expression of "physical processes," or C. is body just an illusion of the rational mind?
Answers that are neither exact nor optimal, but are in some sense "sufficient." This is a result of the essential reliance on heuristic problem-solving methods in situations where optimal or exact results are either too expensive or not possible.?
An attempt to deal with issues of semantic meaning as well as syntactic form.?
Reasoning about the significant qualitative features of a situation.?
A concern with problem solving using inexact, missing, or poorly defined information and the use of representational formalisms that enable the programmer to compensate for these problems. ?
A focus on problems that do not respond to algorithmic solutions. This underlies the reliance on heuristic search as an AI problem-solving technique.?
The use of computers to do symbolic reasoning, pattern recognition, learning, or some other form of inference.?
Little learning from experience. Current expert systems are handcrafted; once the system is completed, its performance will not improve without further attention from its programmers. This leads to severe doubts about the intelligence of such systems.?
Difficulties in verification. Though the correctness of any large computer system is difficult to prove, expert systems are particularly difficult to verify. This is a serious problem, as expert systems technology is being applied to critical applications such as air traffic control, nuclear
Inability to provide deep explanations. Because expert systems lack deep knowledge of their problem domains, their explanations are generally restricted to a description of the steps they took in finding a solution. They cannot tell "why" a certain approach was taken.?
Lack of robustness and flexibility. If humans are presented with a problem instance that they cannot solve immediately, they can generally return to an examination of first principles and come up with some strategy for attacking the problem. Expert systems generally lack this ability.?
Difficulty in capturing "deep" knowledge of the problem domain. MYCIN, for example, lacks any real knowledge of human physiology. It does not know what blood does or the function of the spinal cord. Folklore has it that once, when selecting a drug for treatment of meningitis, MYCIN asked whether
Production systems?
Neural networks?
5 How could an evolutionary process, like GP, be used to evolve
Preferring larger subtrees to smaller ones, and vice versa
Preferring those subtrees that were highly active during the fitness trials
4 The crossover operation used in GP selects a random subtree in both parents. Comment on what you think the effects would be of biasing the random selection according to
3 How might the GP crossover process be changed to allow GP to relax the requirement that the execution of every subtree return a value?
2 Determine what the words genotype and phenotype mean in (biological) evo- lutionary theory. How might these words be used to describe GP?
Control stop lights on a city main street
Control an elevator
1 Specify fitness functions for use in evolving agents that
What changes must be made to the backprop rule for a multilayer, feedforward network if this new error criterion is used?
Explain how your rule differs from the one that uses a squared-error criterion.
Develop an incremental, gradient descent weight change rule for a single sigmoid unit in which the error function is eld-fi, where d is the desired output, f=1/(1-e), s=X W, X is an (n + 1)-dimensional input vector, and W is the (n + 1)-dimensional weight vector being changed.
5 Some Al researchers have argued that the goal of Al should be to build machines that help people in their intellectual tasks rather than to do those tasks. Loosely speaking, "helping" is sometimes called weak AI, and "doing" is sometimes called strong Al. What is your opinion and why?
4 Comment critically on whether or not you think the Turing test is appropriate for deciding whether or not nonhuman machines can "think" Propose at least one alternative.
3 Suppose you were the interrogator in a Turing test. Compose five questions that you would ask of X and/or Y to determine which is a human and which is not.
2 Can you think of any practical advantages for making thinking machines of protein (rather than of silicon)?
1 Give your definition of the word machine. Do you believe that humans are machines? Whatever your belief (perhaps it is either yes, no, maybe, or not entirely), use your definition and evidence about the various abilities of humans to support your belief.
5. Human rights and animal rights are well recognized. Outline a case for or against robot rights.
4. Consider the use of robots and companions for the elderly (or for infants). Investigate and describe briefly the current state of the art for these companions. Present three reasons in favor of their use and three reasons against.
3. There have been proposals made for a global ban on the use of Lethal Autonomous Weapon Systems (LAWS). Investigate and describe the current status of action on a ban on the use of LAWS. Present a brief argument in favor or against such a ban.
2 or neither or both?
2. Find some AI applications and classify the current state-of-the-art for that application in terms of the dimensions. Does the application automate what Kahneman [2011] calls System 1 or System
1. Election Prediction Large corporations do not like unpredictability, so they want a better way to predict the outcome of upcoming elections so they can plan appropriately for future governments. Your company has been asked about the feasibility of building a tool for predicting the results of an

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Artificial Intelligence Foundations Of Computational Agents 2nd Edition David L. Poole, Alan K. Mackworth - Solutions

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