Questions:  For the second test:  note that there are 22 questions; you can expect to be asked to answer 6 or 7 out of 8 or 9.

 

 

  1. List three distinct problems Clark mentions with Marr’s three levels.  Explain briefly.

 

  1. What does it mean to say that the world is its own best model?  (see Clark, page 91).

 

  1. Describe and explain a case where Clark thinks one needs representations and one where he thinks one does not. 

 

  1. Why doesn’t Clark think the brain is best characterized as the seat of reason?

 

  1. Describe why Clark does not think methodological functionalism should be the premiere approach in cognitive science.

 

  1. Explain the difference between weak and strong equivalence.  Why doesn’t strong equivalence require that equivalent systems are made of the same material?

 

  1. What is methodological functionalism?

 

  1. How is folk psychology connected by Dawson with the computational level?

 

  1. How did Hume account for the fact that actions seem to get explained in terms of future possibilities?

 

  1. Why does Dawson think reverse functionalism is essential for connectionists?

 

  1. Consider a neuron obeying McCulloch-Pitts equations.  Show that this neuron can only solve classification problems that are "linearly separable".

 

  1. Define classical conditioning and operant conditioning.  Emphasize their difference.

 

  1. Which components of a neural network are generally used for long-term memory? How does learning occur?

 

  1. State "Hebb's postulate" and discuss the conceptual framework underlying this postulate.

 

  1. What are the limitations of currently available neural networks in learning arbitrarily complex problems?

 

  1. Illustrate the difference between heuristic and algorithmic reasoning by way of an example, but please use an example different from the one(s) found in the notes.

 

  1. A group of graduate students has developed a knowledge based-system for class scheduling. All one has to do is to supply the system with the classes to be offered in a given semester, the available class rooms, and the professors and their specific expertise (plus teaching load). The system will come up with a class schedule showing who will teach what, when and where.
    1. Discuss the knowledge base needed to solve the class scheduling problem. Provide examples of the facts and rules one would expect in such a system.
    2. Suppose you want to extend the system in such a way that it will not schedule two classes at the same time, if these classes are likely to be taken by students in the same semester. What knowledge would you add?

 

  1. Discuss whether the class scheduling problem (i.e., figuring out who should teach which class at what time in which room) is a forward chaining or backward chaining problem (or a combination of both).

 

  1. Describe the components of a knowledge-based system and discuss how realistic it is to use such systems as a metaphor of human intelligence.

 

  1. Describe the design of an intelligent system to determine if a particular artist produced a painting. You may assume that the artist has produced a fairly large number of paintings. Discuss such issues as the knowledge representation and reasoning strategy you would use.

 

  1. Provide an example of a semantic net. Please use original examples, i.e., not ones found in the notes or discusses in class.

 

  1. What learning strategy is (most likely) followed when acquiring the following skills:

a.  Learning to drive a bicycle

b.  Learning a foreign language

c.  Learning the way around town

d.  Learning to speak