1. Take the diagnostic reasoning situation developed in of the Dempster Shafer model of Section…

1. Take the diagnostic reasoning situation developed
in of the Dempster Shafer model of Section 9.2.3 and recast
it as a Bayesian belief network. Compare and contrast these two approaches to
diagnosis.

2. 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
transition probability matrix look like?

3. Consider the behavior of Winstons concept
learning program when learning the concept step, where a step consists of a
short box and a tall box placed

1. Take the diagnostic reasoning situation developed
in of the Dempster Shafer model of Section 9.2.3 and recast
it as a Bayesian belief network. Compare and contrast these two approaches to
diagnosis.

2. 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
transition probability matrix look like?

3. Consider the behavior of Winstons 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 10.25.
Create semantic net representations of three or four examples and near misses
and show the development of the concept.

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