Symbolic Manipulation

Course title

V0545900

Course description

The term "symbolic manipulation (processing)" is used in contrast to "numerical processing" and it deals "formula manipulation" in which mathematical computations such as differentiation, integration, factorization and so on, are processed as they are in mathematical formulas (symbolic strings), or "artificial intelligence" in which knowledges and reasonings are modeled and processed as symbolic strings, in a narrow sense. But in a wide sense, it includes any non-numerical processing like compiler, OS and so on. In this course, we will treat it in a narrow sense. Although this subject is one of lecture courses, it will be proceeded as lecture + exercise. In symbolic manipulation, the programming languages LISP and Prolog are often used. At first, introduction and fundamental exercises of these languages (mainly LISP) will be given. Then, by doing exercises to implement toy models of formula manipulations and expert systems using these languages, fundamental concepts of symbolic manipulations will be studied.

Purpose of class

To understand/study on symbolic processing, which is totally different from numerical processing, with learning the programming languages LISP/Prolog.

Goals and objectives

Understand fundamental concepts of symbolic manipulation and learn basics of the programming language LISP.
Be able to construct applications on LISP by implementing a simple formula manipulation system.
Study fundamentals of expert systems by implementing a simple production system using Prolog.

Language

Japanese

Class schedule

	Class schedule	HW assignments (Including preparation and review of the class.)	Amount of Time Required
1.	Lecture and exercise on following subjects. Introduction to formula manipulation systems	Check the web or references for the symbolic manipulations.	90minutes
1.		Review (including the homework).	100minutes
2.	Data structures in symbolic manipulations	Review the contents of "Data Structures and Algorithms."	90minutes
2.	Data structures in symbolic manipulations	Review (including the homework).	100minutes
3.	LISP (1) Atom, list, basic functions	Check the web or references for the programming language LISP.	90minutes
3.	LISP (1) Atom, list, basic functions	Review (including the homework).	100minutes
4.	LISP (2) Variables, functional definitions, recursive calls	Preparations for the lecture.	90minutes
4.	LISP (2) Variables, functional definitions, recursive calls	Review (including the homework).	100minutes
5.	LISP (3) Predicates, conditions	Preparations for the lecture.	90minutes
5.	LISP (3) Predicates, conditions	Review (including the homework).	100minutes
6.	LISP (4) Some list processing (recursion, map functions)	Preparations for the lecture.	90minutes
6.	LISP (4) Some list processing (recursion, map functions)	Review (including the homework).	100minutes
7.	LISP (5) Some list processing (efficient processing using destructive functions)	Preparations for the lecture.	90minutes
7.		Review (including the homework).	100minutes
8.	Formula manipulation (1) Internal representations of mathematical formulas	Preparations for the lecture.	90minutes
8.		Review (including the homework).	100minutes
9.	Formula manipulation (2) Input/output of mathematical formulas (syntax analysis, pretty-print)	Preparations for the lecture.	90minutes
9.		Review (including the homework).	100minutes
10.	Formula manipulation (3) Symbolic differentiation and symplification of mathematical formulas	Preparations for the lecture.	90minutes
10.		Review (including the homework).	100minutes
11.	Formula manipulation (4) Symbolic integration	Preparations for the lecture.	90minutes
11.	Formula manipulation (4) Symbolic integration	Review (including the homework).	100minutes
12.	Expert system (1) Symbolic logic and logic programming language Prolog	Preparations for the lecture.	90minutes
12.		Review (including the homework).	100minutes
13.	Expert system (2) Production systems	Preparations for the lecture.	90minutes
13.	Expert system (2) Production systems	Review (including the homework).	100minutes
14.	Final examination and review	Review the all of lectures.	190minutes
Total.	-	-	2660minutes

Relationship between 'Goals and Objectives' and 'Course Outcomes'

	Exermination	Exercises	Total.
1.	20%	20%	40%
2.	20%	20%	40%
3.	10%	10%	20%
Total.	50%	50%	-

Evaluation method and criteria

Examinations (50%) and exercises (50%).

Textbooks and reference materials

No textbook.

Prerequisites

"Data Structures and Algorithms", "Programming Exercises."

Office hours and How to contact professors for questions

Tuesday 12:35 -- 13:05.

Relation to the environment

Non-environment-related course

Regionally-oriented

Non-regionally-oriented course

Development of social and professional independence

Course that cultivates a basic problem-solving skills

Active-learning course

About half of the classes are interactive

Course by professor with work experience

Work experience	Work experience and relevance to the course content if applicatable
N/A	該当しない

Last modified : Thu Mar 21 14:08:46 JST 2019