Cognitive Science 170
Natural and Artificial Symbol-Using Systems

Name: _________________________


Questions: (3-6 pages). (i) Choose question 1 or 2! (ii) indicate at beginning of paper which question you have chosen! (iii) hand in a paper printout in class, and (iv) staple the pages together (don't send an email attachment).

1. Fodor and Pylyshyn criticize many different features of neural network models. Pick out *one* of their main arguments, describe it, and apply it to at least one example of a 'real' neural network model and a 'real' AI model.

2. Turing originally conceived of computation as automated conscious calculation of the sort that a human can do. Several decades later, practical computer architectures (von Neumann architecture) and high-level programming languages (e.g., LISP, production system languages) were developed. People such as Allen Newell suggested that the upper level cognitive architecture implemented in these high-level languages (as opposed to low-level machine architecture or language) was crucial to understanding human cognition. Support or argue against this idea using example of at least one 'real' neural network model and one 'real' AI model.

In both cases, you can argue either side of the issue. I won't penalize or reward you for taking either side (or for arguing for something in between). The most important thing is to cite at least one example of a connectionist model and one example of a more traditional artificial intelligence model (like the ones presented in class but not limited to them) to support your arguments. Examples will make your task easier. Note that Fodor and Pylyshyn cite only trivial examples, so I am asking you to go beyond what they have done.

Finally, it is almost always a good idea to start each paragraph with a topic sentence. A good test of the organization of your paper is to read aloud just the topic sentences, one after the other, and see if it makes reasonable sense.

due beginning of class Mon, 10/23/06