CS 30 Homework 10

1. Finish the Jets and Sharks network implementation from Lab 12. In your definition of new-unit, include an extra state variable called graphics-painter (initialized to #f), and add the following two methods to new-unit:

   (define method:get-painter
     (lambda () graphics-painter))
   
   (define method:set-painter
     (lambda (painter)
       (set! graphics-painter painter)
       'ok))
   

   These methods will enable you to use the simple user interface defined in the file js-graphics.scm. Loading this file into DrScheme will create a graphics window that displays the activations of all units in the network (positive activations are shown in green, negative in red). Put this file in the same folder as your Jets and Sharks program, and then add the following line to the end of your code, after the section that creates all of the network units and connections:

   (load "js-graphics.scm")
   

2. This file also defines the following useful commands:
   • (show-active) prints out all units with positive activations
   • (show-clamped) prints out all clamped units
   • (clamp unit1 unit2 ...) clamps the specified units
   • (clear unit1 unit2 ...) unclamps the specified units
   • (clear-all) unclamps all units in the network
   • (reset-network) unclamps all units and resets their activations to the resting level
   • (run n) runs the network for n cycles

   Perform the following test to make sure your network updates the activations of all units correctly:

   1. (reset-network)
   2. (clamp ken)
   3. (run 100)
   4. (show-active)
   The resulting activations should match the values shown below:

   Sharks: 0.5064877987024132
   H.S.: 0.5244301902932138
   Single: 0.5064877987024132
   Burglar: 0.3783457617251305
   20s: 0.37822356300799614
   30s: 0.005074536937235068
   Ken: 0.8064494010682347
   (pete): 0.03816710007054064
   (fred): 0.03816710007054064
   (nick): 0.23830693996726438
   (ken): 0.6832206158490971
   (earl): 0.038167100070540715
   (rick): 0.03835619534961257
   (neal): 0.23830693996726438
   

   If your network generates the above values, you are ready to investigate the properties of the memory model. Answer the following questions as clearly as you can.

3. Retrieving an individual from their name. After performing the test in Part 2, why are some of Ken's properties more strongly activated than others? None of the other name units are activated, yet several other instance units are active. Why is this?

4. Retrieval from a partial description. Ken can be uniquely described by two properties: his gang and his age. Reset the network, then clamp the units sharks and 20s. Run the network for 100 cycles. What are the main differences between this state and the state at the end of Part 2? Why do the occupation units show partial activations of units other than Ken's occupation (Burglar)?

5. Graceful degradation. To investigate the effect of erroneous information in the probe supplied to the network, first run the network with all of Ken's properties other than his name clamped. Then try it again with junior-high clamped in place of high-school. How well does the model do with the "noisy" version of Ken compared to the correct version? Would it do this well with all noisy versions of individuals? Test with at least one other individual, and explain what happens.

6. Default assignment. Sometimes we don't know something about an individual; for example, we may never have been exposed to the fact that Lance is a burglar. Yet we are able to give plausible guesses about such missing information. The network can do this too. To see this, we will erase the network's explicit knowledge that Lance is a burglar by disabling the connections between the instance unit for Lance and the Burglar unit. But first we need a way to temporarily disable connections between units.
   1. Add methods to new-connection called disable and restore, both of which take no arguments. Disable should set the strength of the connection to 0; restore should set it back to its original value.
   2. Add methods to new-unit called disable-connection-from and restore-connection-from, both of which take another unit u as an argument. These methods should scan the list of incoming connections for one whose from-unit matches u (use the equal? test here), and then either disable or restore the connection.
   3. For convenience, define the user interface commands (cut unit1 unit2) and (restore unit1 unit2), to make it easy to disable or restore the bi-directional connections between unit1 and unit2.

   Now run the network for 100 cycles with lance clamped, to see what happens with all connections intact. Next, reset the network, disable the connections between Lance's instance unit (instance-lance) and the burglar unit, and run the network again for 100 cycles with lance clamped. Was the network able to fill in Lance's occupation correctly? What is the resulting activation level of the burglar unit in each case?

7. Spontaneous generalization. Now let's consider the network's ability to retrieve appropriate generalizations over sets of individuals—that is, its ability to answer questions like "What are Jets like?" or "What are people who are in their 20s and have only a junior high education like?" (Note: Be sure to restore the connections between burglar and instance-lance before going on.) Ask the network to generalize about the Jets by clamping the jets unit and cycling for 100 steps. What is the general profile of a Jets gang member, according to the network? Next, ask it to generalize about people in their 20s with a junior high education by clamping 20s and junior-high. What can be said about the other properties of this type of person, in general?

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