Welcome to Music 80L

1. Welcome to Music 80L Artificial Intelligence and Music

2. Class Website http://artsites.ucsc.edu/faculty/cope/music80l.html There you’ll find the syllabus in PDF format for downloading. You will also find the Powerpoint presentations as the classes are completed as well as exercises, links, etc. In other words, this site is your bedrock place for all of the time you’re not in class.

3. Don’t forget: • http://artsites.ucsc.edu/faculty/cope/music80l.html

4. Course syllabus • Music 80L • Artificial Intelligence and Music • David Cope Winter 2011 • email: howell@ucsc.edu • WWW: http://arts.ucsc.edu/faculty/cope/music80L • Office Hours: T/Th 12-2 • Office: Digital Arts Research Center (DARC), Room 337. • TAs: • Jonathan Hoefs, jhoefs@ucsc.edu • Andre Marquetti. amarque3@ucsc.edu • Fernanda Navarro. nandanavarro@gmail.com

5. Continued • Artificial Intelligence and Music covers the basics of algorithmic music composition as well as artificial life, machine learning, grammars, neural nets, genetic algorithms, agents, and Markov techniques, music analysis, and composition. This course meets T/Th from 10-11:45 in the Recital Hall in the Music Center (Room 101). Lecture PowerPoints will be posted for download. • Textbook: Computer Models of Musical Intelligence. (Baytree) • Two Exams. Midterm = 100 multiple-choice questions. Final = 200 multiple-choice questions. Final project will consist of 1) a short (5-20 pages) and intelligible paper; and 2) a tape of 4 or more representative outputs – both due at the final exam period.

6. Continued • Attendance: Taken at each class session (often at 10 AM). More than three unexcused absences equates to a fail. Email excuses to any of the TAs. No eating or drinking in classroom. Bikes not allowed. Computers acceptable but monitored by TAs. • Grades not computed on a curve. Everyone can get an A, a C, or an F. Reviews for test given class prior and at other times during the quarter as well as examples of paper, etc. Come to class, study hard, you’ll do well and not have to compete with others for your grade.

7. Continued • Week (subject to change) • 1. History, Background, and Definitions (Terms, History, Musical Algorithms, Early • Programs). • 2. Basic Music and A-Life Rudiments, • Notation, Computers, and using Lisp code Program for Class. Game of Life. Swarms. • 3. Music Representation and MIDI, Genetic Algorithms, and Cellular Automata. • Melody. • 4. Simple Mathematical Types: Stochastics, Fractals, and Chaos. Markov Sequences. • Harmony. Music analysis. • 5. Patterns and Music Experiments in Musical Intelligence. Music Composition. • Association Networks. Musical Form and Instrumentation. • 6. Mid-term Exam (Feb. 14, Tues., class time). Artificial Neural Networks, basic concepts of the Black Box, Hidden Units, Training, and Back Propagation. Music Counterpoint. • 7. Agents, Machine Learning. Music Composition. • 8. Other Techniques, Programs, and Approaches. • 9-10. Project Presentation and Performances. Review. Final exam (March 20, 12-3).

8. Continued • Balaban, Mira, Kemal Ebcioglu, and Otto Laske. 1992. Understanding Music with AI. • Cambridge: MIT Press. [Q335.U55] • Cope, David. 1991. Computers and Musical Style. Madison, Wisc.: A-R Editions.[MT 723.C68] • Cope, David. 2005. Computer Models of Musical Creativity. Cambridge, MA.: MIT Press. [MT41 .C67] • Cope, David. 1996. Experiments in Musical Intelligence. Madison, Wisc.: A-R Editions. • Cope, David. 2007. Hidden Structure; Music Analysis Using Computers. Madison, Wisc.: A-R Editions. [ML74 .C69 2008] • Cope, David. 2000. The Algorithmic Composer. Madison, Wisc.: A-R Editions. [MT56 .C668] • Cope, David. 2001. Virtual Music. Cambridge, MA.: MIT Press. [MT56 .C69] • Hawkins, Jeff. 2004. On Intelligence. New York: Henry Holt. [QP376 .H294] • Hiller, Lejaren, and Leonard Isaacson. 1959. Experimental Music. New York: • McGraw-Hill. [MT 41.H58] • Hofstadter, Douglas. 1995. Fluid Concepts and Creative Analogies. NY: Basic Books. [BF 311.H617] • Levy, Steven. 1992. Artificial Life. New York: Vintage Books. [QA76.87.L49] • Noyes, James. 1992. Artificial intelligence with Common Lisp: Fundamentals of Symbolic and Numeric Processing. Lexington, MA: D.C. Heath. [QA76.73.C62 N68] • Rowe, Robert. 1993. Interactive Music Systems: Machine Listening and Composing. Cambridge: MIT Press. [MT 723.R7] • Russell, Stuart J. and Peter Norvig. 2010. Artificial Intelligence: A Modern Approach. Upper Saddle River: Prentice Hall. [Q335 .R86] • Schwanauer, Stephan and David Levitt. 1993. Machine Models of Music. Cambridge: MIT Press. [ML 74.3.M3] • Todd, Peter and Gareth, Loy. 1991. Music and Connectionism. Cambridge: MIT Press. [ML 1093.M86] • Winsor, Phil. 1987. Computer-Assisted Music Composition. Princeton, NJ: Petrocelli Books. [MT 56.W56] • Winston, Patrick Henry. 1984. Artificial Intelligence. Reading, MA: Addison Wesley. [Q335.W56] • Wolfram, Steven. 2002. A New Kind of Science. Champaign, Ill: Wolfram Media. [QA267.5.C45 W67] • Xenakis, Iannis. 1971. Formalized Music. Bloomington: Indiana University Press. [ML 3800.X4]

9. Class rules. 1) be on time (earlier if possible) – I will have role taken in writing each class. 2) no food or drink (except water in bottles) allowed 3) no bikes – park them outside in the bike racks.

10. 4) No playing computer games or texting in class. We’ll be watching. 5) turn off your cell phones or be surprised.

11. Two Exams: Midterm = 100 multiple-choice questions. Final = 200 multiple-choice questions. Lots of review in class and on website.

12. There will be several small assignments (three of four) during the quarter that must be turned in at the next class period. Failing to do so will be the same as an unexcused absence.

13. Final project will consist of 1) a short (5-20 pages) and intelligible paper; and 2) a tape of 4 or more representative outputs – both due at the final exam period.

14. All software used in class except that which you choose yourself will be free and available in one form or another.

15. PowerPoint • Every PowerPoint that I use in class will appear on the class website within the next day or two after the class for your review.

16. Me? (FYI) Been working as a composer for sixty years, as a programmer for thirty-four years. Seven books on the subject of AI and Music. Many CDs of computer-composed music. Taught courses at undergrad and grad levels in AI and Music including programming.

17. Don’t forget: • http://artsites.ucsc.edu/faculty/cope/music80l.html

18. Course will basically cover two linked double areas: 1) Artificial Life; Artificial Intelligence 2) Music Analysis; Music Composition Most importantly how these two branches can usefully intersect.

19. Definitions

20. Life: Life has been defined in different ways, including the abilities to: 1 grow 2 reproduce 3 adapt 4 metabolize 5 react 6 move 7 die 8 use DNA 9 form from carbon 10 survive

21. One person’s thoughts: “A ‘thing,’ something separate and distinct. This ‘thing’ exists within an environment. It’s able to move around in that environment, and can ingest aspects of that environment. It can access that ingestion for advantage, and excrete the remains. It procreates in some way, and has some means of communication with other objects of like kind. It can inherit characteristics from its parent or parents. Something biologists call crossover. Mutation is possible during procreation, but not common. Contains a desire to continue to exist, but must die at some point. It’s children carry on.”

22. Maybe life is just something that adapts rather than accepts. Life evolves over time to match its environment successfully. Rocks simply accept whatever the environment gives it. Or maybe rocks adapt on a much slower time scale and everything is alive? You’d be surprised how many people think this is true.)

23. Enjoy.

24. Your additions? Take out a blank sheet of paper and tell me. Print your name at the top clearly. This is role for today!!!!!!!

25. We have to come to some conclusion to proceed usefully. We’ll use: 1. Metabolize 2. Evolve (adapt) 3. Reproduce

26. Intelligence: Intelligence has been defined in different ways, including the abilities to have: 1 abstract thought 2 understanding 3 communication 4 reasoning 5 learning 6 problem solving 7 intuition 8 deduction 9 induction

27. “The ability to analyze, associate, and adapt. All three must be present for intelligence to exist. All the rest, the intuitive, consciousness, religious, death, and so on, are mythical attributes that humans have proclaimed to advantage themselves over many other intelligent creatures.”

28. Enjoy.

29. Your additions?

30. We have to come to some conclusion to proceed usefully. We’ll use: 1. Learn 2. Reason 3. Abstract

31. Music Analysis: 1 reduction 2 identifications 3 relationships 4 patterns 5 resolutions 6 motives 7 form 8 texture 9 rhythm 10 themes

32. “Music analysis is the desire to understand the implicit meaning in music. To come to grips with the ‘between the lines’ of what we hear.” “The wonder of music is that it has no meaning. We give it meaning. Each of us. Independently.”

33. Enjoy.

34. Your additions?

35. We have to come to some conclusion to proceed usefully. We’ll use: 1. Reduction 2. Identification 3. Structure

36. Music Composition 1 ideas 2 repetition 3 variation 4 harmony 5 counterpoint 6 development 7 form 8 texture 9 rhythm 10 themes

37. “Composing music requires an understanding of the professional aspects of the profession, the interpretation of personal meaning in sound, and the profound acceptance of talent; of one’s innate abilities.” “Music is organized sound.”

38. Enjoy.

39. Your additions?

40. We have to come to some conclusion to proceed usefully. We’ll use: 1. Ideas 2. Form 3. Development

41. Some additional terms Algorithm: A step by step process used to solve a problem. Can be paper as well as computational. (notice the spelling: rithm versus rhythm)

42. Hmmm.

43. Random (indeterminate, chance): Doesn’t exist except possibly t the quantum level. What we perceive as random (toss of a coin, function on a computer, atoms in a sea wave) are determinate. Just too complicated to figure out. Computer randomness is simply irrelevant elements making choices (usually the computer inner clock), and often called pseudo-random by computer scientists. I use the term pseudo-random to ensure we’re not talking about something called fundamental randomness. Actions for which there are no causes. Even quantum mechanics randomness remains controversial.

44. Enjoy.

45. Mathematics: Addition, subtraction, multiplication, division, algebra, geometry, and calculus, and so on, concerned with the study of number, quantity, shape, and space and their interrelationships by using a specialized notation. Note that determinate mathematics cannot create indeterminate output. Indeterminate mathematics must contain a symbol that itself is random only because we say it’s so.

46. Hmmm.

47. Discrete mathematics: Deals with discrete rather than continuous numbers. This means that separate numbers have unique qualities we’re interested in. Prime numbers are a good example. Non continuous. Some break discrete math into three general areas: combinatorics, iteration and recursion, and vertex-edge graphs.

48. Logic.

49. Math, computers, music are all easy subjects. Teachers make them hard. We’ll make them easy. No intimidation allowed here.

50. Let’s give it a try with yet four new terms. Induction Deduction Phenotype Genotype