Assignment 1: Python Warm-up and Chatbot |
CSE 415: Introduction to Artificial Intelligence The University of Washington, Seattle, Spring 2019 |
The reading for this assignment is
Python as a Second Language.
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Due Wednesday, April 10,
at 23:59 PM.
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Overview: Part A of this assignment consists of several smallish Python puzzles. If you are new to Python, do the associated reading. Otherwise, this is mainly a refresher with a little problem-solving thrown in. Part B is an opportunity not only to practice your Python skills, but also to get creative and produce an agent with "character." Even more, it will offer you a chance to interact with another member of the class to create a dialog between your conversational agents. If the conversation is "good," you can get extra credit. You should turn in four files: (1) a file named a1.py of function definitions, (2) a file a1ExamplesPlus.txt of example calls, results and answers to questions, (3) a file containing the Python code for your conversational agent (named as described in the instructions), and (4) a text file sampleConversation.txt containing a sample dialog between your agent and your partner's agent (see instructions for details).
For the file of examples,
you can use a combination of input and output together with
comment lines (beginning with a pound sign) to show that you
have verified each of your answers on the computer.
For each function, show a demonstration on the same example shown on this page,
and two additional examples: one shorter (or smaller),
and one longer (or larger) and more interesting
(use your imagination).
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Part A. Defining Functions (30 points).
Write Python function definitions for the following requirements (worth 5 points each, except for numbers 2 and 4, which are worth 10 points each). You should be able to infer what each function should do by a combination of reading its name and examining the relationship between its input and ouput on the given examples. Note that the functions that accept lists as arguments must be able to handle lists of any length. For this assignment your functions do not have to validate the types of their inputs. That is, you may assume that they will be called with arguments of the proper types. 1. three_x_cubed_plus_7(2) -> 31 2. triple_up([2, 5, 1.5, 100, 3, 8, 7, 1, 1, 0, -2]) -> [[2, 5, 1.5], [100, 3, 8], [7, 1, 1], [0, -2]] 3. mystery_code("abc Iz th1s Secure? n0, no, 9!") -> "NOP vM GU1F fRPHER? A0, AB, 9!" (Hint: If a character of the input is alphabetic, then it undergoes a change of case as well as a mapping to a different place in the alphabet.) 4 future_tense(['Yesterday', 'I', 'ate', 'pasta', 'and', 'today', 'I', 'am', 'having', 'soup']) -> ['Tomorrow', 'I', 'will', 'eat', 'pasta', 'and', 'tomorrow', 'I', 'will', 'be', 'having', 'soup'] future_tense(['Life', 'is', 'good', 'now']) -> ['Life', 'will', 'be', 'good', 'tomorrow']Use the following rules for forming the future tense: Recognize past and present-tense forms of the verbs to be, to go, to eat, to have, and to do. Optionally handle some other verbs. Recognize the words today, yesterday, and now, and change them to tomorrow. The above exercises will be graded with a combination of autograder and manual grading. Exercises 1 and 2 are worth 5 points each. Three points will be awarded for passing the instructors' autograder tests, and one point will awarded for giving each required example in your a1examplesPlus.txt file. Exercises 3 and 4 are worth 10 points each, with 6 of the points given for passing the autograder tests and 2 points for each required example.
A simple "sanity-check" testing program is available
that might help you realize
that you have a spelling error in a function name or that your functions do not
return values of the proper type:
a1_fn_sig_checker.py.
Note that this file is not an autograder, and it does NOT
test whether your functions compute the correct values.
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Part B. Conversational Agents (70 points).
Create a Python program that simulates a human character in a dialog. Your program should have some definable personality, such as a widget salesman, entertainment star, political figure, etc. Besides being able to carry on a conversation with a human user, it should be able to join into conversations with the agents created by any member of the class. To do this, it will need to implement certain functions with a strict protocol. Your solution should follow these guidelines:
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Turn-In Instructions Turn in your files, named according to the instructions above, at our course's Canvas website. |
Updates and Corrections
Note: In the future-tense function, handling of negation with the verb do is optional, not required. For example "We didn't eat." should map to "We will not eat.", but you don't have to handle that kind of sentence. Also, you don't have to handle the use of do as a helping verb, as in "We do eat meat.". (April 8). Minor adjustments made on April 1. If needed, additional updates and corrections will be posted here, and/or in Piazza. |