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management and artificial intelligence

Questions and Answers of Management And Artificial Intelligence

This 24 element vector would be the input value for your net. You would build your own training vectors. Do the same task with a counterpropagation net; compare your results.
Use a backpropagation net to recognize the ten (hand drawn) digits. One approach would be to build a 4 x 6 array of points. When a digit is drawn on this grid it will cover some elements, giving them
Write a counterpropagation net to solve the exclusive-or problem. Compare your results with those of the backpropagation net of Section 11.3.3. Use your counterpropagation net to discriminate between
Write a Kohonen net in LISP or C++ and use it to classify the data of Table 11.3. Compare your results with those of Sections 11.2.2 and 11.4.2.
Build a backpropagation network in LISP or C++ and use it to solve the exclusive-or problem of Section 11.3.3. Solve the exclusive-or problem with a different backpropagation architecture, perhaps
Build a perceptron net in LISP and run it on the classification example of Section 11.2.2.a. Generate another data set similar to that of Table 11.3 and run your classifier on it.b. Take the results
Make a McCulloch−Pitts neuron that can calculate the logic function implies, ⇒.
Another problem type excellent for reinforcement learning is the so-called gridworld. We present a simple 4 × 4 gridworld in Figure 10.26. The two greyed corners are the desired terminal states for
Can you analyze the inverted pendulum problem, Figure 9.8, presented in Section 9.2.2 from a reinforcement learning perspective? Build some simple reward measures and use the temporal difference
Analyze Samuel’s checker playing program from a reinforcement learning perspective.Sutton and Barto (1998, Section 11.2) offer suggestions in this analysis.
What happens if the temporal difference algorithm of Problem 13 plays tic-tac-toe against itself?
Consider the tic-tac-toe example of Section 10.7.2. Implement the temporal difference learning algorithm in the language of your choice. If you designed the algorithm to take into account problem
Develop an explanation-based learning algorithm in the language of your choice. If you use PROLOG, consider the algorithms developed in Section 15.8.3.
Develop a domain theory for explanation-based learning in some problem area of your choice. Trace the behavior of an explanation-based learner in applying this theory to several training instances.
From Quinlan (1993) obtain the C4.5 decision tree algorithm and test it on a data set.There are complete programs and data sets for C4.5 available from this reference.
Other problems of ID3 are bad or missing data. Data is bad if one set of attributes has two different outcomes. Data is missing if part of the attribute is not present, perhaps because it was too
Discuss problems that can arise from using continuous attributes in data, such as a monetary cost, dollars and cents, or the height, a real number, of an entity. Suggest some method for addressing
Implement ID3 in a language of your choice and run it on the credit history example from the text. If you use LISP, consider the algorithms and data structures developed in Section 16.13 for
Develop a simple table of examples in some domain, such as classifying animals by species, and trace the construction of a decision tree by the ID3 algorithm.
Using Shannon’s formula, show whether or not a message about the outcome of a spin of a roulette wheel has more information than one about the outcome of a coin toss. What if the roulette wheel
Using the information theoretic selection function of Section 10.4.3, show in detail how ID3 constructs the tree of Figure 10.14 from examples in Table 10.1. Be sure to show the calculations used in
Build the version space search algorithms in PROLOG, or the language of your choice. If you use PROLOG, see hints in Section 15.14.1.
The run of the candidate elimination algorithm shown in Figure 10.9 does not show candidate concepts that were produced but eliminated because they were either overly general, overly specific, or
Consider the behavior of Winston’s concept learning program when learning the concept“step,” where a step consists of a short box and a tall box placed in contact with each other, as in Figure
Given that you wanted to design a second-order Markov model, i.e., where each observable state would be dependent on the previous two observable states. How would you do this?What would the
Take the diagnostic reasoning situation developed in Tables 9.1 and 9.2 of the Dempster–Shafer model of Section 9.2.3 and recast it as a Bayesian belief network. Compare and contrast these two
Create cliques and a junction tree for the following situation (seen in Figure 9.23). Robbery, vandalism and an earthquake can all set off (cause) a house alarm. There is also a measure of the
Create a Bayesian belief diagram for another application, for example medical diagnosis, geological discovery, or automobile fault analysis. Point out examples of d-separation and create a clique
Create an algorithm for Bayesian belief propagation and apply it to the slippery sidewalk domain of Section 9.3.2. You might use Pearl’s (1988) message passing approach or the clique triangulation
Complete the symbolic evaluations that are required to finish Table 9.4.
Put another link in Figure 9.16, say connecting season directly to slick sidewalk and then create a clique tree to represent this situation. Compare the complexity issues with those of the clique
Go to the literature, for example Ross (1995), and describe two other areas where fuzzy control might be appropriate. Construct a set of fuzzy rules for those domains.
Write a program that implements the fuzzy controller of Section 9.2.2.
Continue the inverted pendulum example of Section 9.2.2 with two more iterations of the controller where the output of one iteration is the input values for the next iteration.
Reasoning by assumption of a minimum model is important in human everyday life. Work out two more examples that assume minimum models.
Create another reasoning network similar to that of Figure 9.4 and show the dependency lattice for its premises, as was done in Figure 9.5.
Use the schema axioms presented in McCarthy (1980, Section 4) to create the circumscription results presented in Section 9.1.3.
Create a new example of diagnostic reasoning and use the Dempster–Shafer equations of Section 9.2.3 to obtain belief distributions as in Tables 9.1 and 9.2.
Consider the simple MYCIN-like rule: if A ∧ (B v C) ⇒ D (.9) ∧ E (.75). Discuss the issues that arise in capturing these uncertainties in a Bayesian context. How might this rule be handled in
Given the following rules in a “back-chaining” expert system application:A ∧ not(B) ⇒ C (.9)C v D ⇒ E (.75)F ⇒ A (.6)G ⇒ D (.8)The system can conclude the following facts (with
Identify three application domains where reasoning under conditions of uncertainty is necessary. Pick one of these areas and design six inference rules reflecting reasoning in that domain.
Expand the propositional calculus representation scheme introduced by Williams and Nayak(1996a, p. 973) for describing state transitions for their propulsion system.
Read Williams and Nayak (1996, 1996a) for a more complete discussion of their modelbased planning system.
In Section 8.4.3 we presented a planner created by Nilsson and his students at Stanford(Benson and Nilsson 1995). Teleo-reactive planning allows actions described as durative, i.e., that must
Read the ABSTRIPS research (Sacerdotti 1974) and show how it handles the linearity (or incompatible subgoal) problem in planning.
Show two more incompatible (precondition) subgoals in the blocks world operators of Figure 8.19.
Design an automated controller that could use add and delete lists to generate a graph search similar to that of Figure 8.19.
Use add and delete lists to generate the search space of Figure 8.19.
Show how the add and delete lists can be used to replace the frame axioms in the generation of STATE 2 from STATE 1 in Section 8.4.
Use the operators and frame axioms of the previous question to generate the search space of Figure 8.19.
Create the remaining frame axioms necessary for the four operators pickup, putdown, stack, and unstack described in rules 4 through 7 of Section 8.4.
Read and comment on the survey paper Improving Human Decision Making through Case-Based Decision Aiding by Janet Kolodner (1991).
If no software is available, consider building such a system in PROLOG, LISP, or Java.
Use commercial software (check the WWW) for building the case-based reasoning system of Exercise
Build a case-based reasoner for an application of your choice. One area might be for selecting computer science and engineering courses to complete an undergraduate major or a MS degree.
Read one of the early papers using model-based reasoning to teach children arithmetic(Brown and Burton 1978) or electronic skills (Brown and VanLehn 1980). Comment on this approach.
Read and comment on the paper Diagnosis based on description of structure and function(Davis et al., 1982).
Create a model-based reasoning system for a simple electronic device. Combine several small devices to make a larger system. You can use if... then... rules to characterize the system functionality.
What are its strengths and weaknesses? What would you do to improve it? Was it appropriate to your problem? What problems are best suited to that tool?
Critique the shell you used for Exercise
Implement an expert system using a commercial shell program. These are widely available for personal computers as well as larger machines. We especially recommend CLIPS from NASA (Giarratano and
Pick another area of interest for designing an expert system. Answer Exercises 1–3 for this application.
Consider the graph of Exercise 2 above. Do you recommend data-driven or goal-driven search? breadth-first or depth-first search? In what ways could heuristics assist the search?Justify your answers
Take Exercise 1 above. Create in English or pseudocode 15 if... then... rules (other than those prescribed in Section 8.2) to describe relations within this domain. Create a graph to represent the
In Section 8.2 we introduced a set of rules for diagnosing automobile problems. Identify possible knowledge engineers, domain experts, and potential end users for such an application. Discuss the
Suppose you were designing an agent system to represent an American football or alternatively a soccer team. For agents to cooperate in a defensive or in a scoring maneuver, they must have some idea
There were a number of important issues presented near the end of Section 7.4 related to the creation of agent-oriented solutions to problems. Pick one of these and discuss the issue further.
Identify five properties that an agent language should have to provide an agent-oriented internet service. Comment on the role of Java as a general-purpose agent language fo building internet
At the end of Section 7.3.1, there are five potential issues that Brooks’ subsumption architecture (1991a) must address to offer a successful general-purpose approach to problem-solving. Pick one
Brooks’ paper (1991a) offers an important discussion on the role of representation in traditional AI. Read this paper, and comment on the limitations of explicit, general-purpose representational
Describe a representation that could be used in a program to solve analogy problems like that in Figure 7.30. This class of problems was addressed by T. G. Evans (1968). The representation must be
Two examples of analogical reasoning were presented in Section 7.3. Describe an appropriate representation and search strategy that would allow for identification of the best answer in each
Each of the following sequences of characters is generated according to some general rule.Describe a representation that could be used to represent the rules or relationships required to continue
Construct a type hierarchy in which some types do not have a common supertype. Add types to make this a lattice. Could this hierarchy be expressed using tree inheritance? What problems would arise in
Construct a hierarchy of subtypes for the concept vehicle; for example, subtypes of vehicle might be land_vehicle or ocean_vehicle. These would have further subtypes. Is this best represented as a
Using conceptual dependencies, define a script for:a. A fast-food restaurant.b. Interacting with a used-car salesperson.c. Going to the opera.
Give evidence from your own experience that suggests a script-like or frame-like organization of human memory.
Translate the financial advisor knowledge base, Section 2.4, into conceptual graph form.
Translate the conceptual graphs of Figure 7.29 into predicate calculus.
Define a specialized representation language to describe the activities of a public library.This language will be a set of concepts and relations using conceptual graphs. Do the same thing for a
Specialization of conceptual graphs using join and restrict is not a truth-preserving operation. Give an example that demonstrates that the restriction of a true graph is not necessarily true.
The operations join and restrict define a generalization ordering on conceptual graphs. Show that the generalization relation is transitive.
Translate the conceptual graphs of Figure 7.29 into English sentences.
Read “What’s in a Link” by Woods (1985). Section IV of this article lists a number of problems in knowledge representation. Suggest a solution to each of these problems using logic, conceptual
In Section 7.2.1 we presented some of the arguments against the use of logic for representing common sense knowledge. Make an argument for the use of logic in representing this knowledge.
Section 6.2.3 presented the general conflict resolution strategies of refraction, recency, and specificity. Propose and justify two more such strategies.
Using predicate calculus as a representation language:a. Write the problem explicitly as a production system.b. Generate the state space and stages of working memory for the data-driven solution to
Consider the financial advisor problem discussed in Chapters 2, 3, and
Using the goal and start states of Figure 6.5, hand run the production system solution to the 8-puzzle:a. In goal-driven fashion.b. In data-driven fashion.
Using the rule in Example 6.2.3 as a model, write the eight move rules needed for the full 8× 8 version of the knight’s tour.
Write the pseudo-code definition for a breadth-first version of pattern_search (Section 6.1.2). Discuss the time and space efficiency of this algorithm.
Using the move and path definitions for the knight’s tour of Section 6.1.2, trace the execution of pattern_search on the goals:a. path(1,9).b. path(1,5).c. path(7,6).When the move predicates are
Trace the execution of the recursive depth-first search algorithm (the version that does not use an open list) on the state space of Figure 3.14.
a. Write a member-check algorithm to recursively determine whether a given element is a member of a list.b. Write an algorithm to count the number of elements in a list.c. Write an algorithm to count
Three prisoners, A, B, C, are in their cells. They are told that one of them will be executed the next day and the others will be pardoned. Only the governor knows who will be executed.Prisoner A
Suppose an automobile insurance company classifies a driver as good, average, or bad. Of all their insured drivers, 25% are classified good, 50% are average, and 25% are bad.Suppose for the coming
The expectation is the mean or average of the value of a random variable. In throwing a die, for example, it can be calculated by totaling up the resulting values from a large number of throws and
a. Create an algorithm for heuristically searching and/or graphs. Note that all descendants of an and node must be solved to solve the parent. Thus, in computing heuristic estimates of costs to a
Perform alpha-beta pruning on the tic-tac-toe search of Figures 4.23, 4.24, and 4.25. How many leaf nodes can be eliminated in each case?
Perform a right-to-left prune on the same tree. Discuss why a different pruning occurs.

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