SYMSYS 275 / BIO 175

SYMSYS 275/BIO 175
Collective Behavior and Distributed Intelligence
An Interdisciplinary Workshop

2016-2017 Spring Quarter, Stanford University

SYMSYS 275 / BIO 175: 3 units, Ltr-CR/NC

Instructors: Todd Davies and Deborah Gordon
(with assistance from Bernardo Huberman)

Wednesdays 4:30-5:20pm

Room 460-126 (Margaret Jacks Hall, first floor)

Public website: http://web.stanford.edu/class/symsys275/
Discussion forum (for class members only): http://piazza.com/stanford/spring2017/symsys275/home

Birds flying in formation, from
https://www.pexels.com/photo/v-formation-of-bird-during-daytime-62667/,
License CC0

This version: June 2, 2017

Course Description

This course will explore possibilities for student research projects based on presentations of faculty research. We will cover a broad range of topics within the general area of collective behavior and distributed intelligence, in both natural and artificial environments. Students will build on faculty presentations to develop proposals for future projects. Enrollment is limited to 20 students.

Intended Population

The course is open to both undergraduates and graduate students, but is especially aimed at undergraduates who are looking to get involved in research with faculty related to collective behavior.

Format

The course is a workshop, featuring presentations by faculty of their research, backed by appropriate readings. Students will be expected to write short reaction pieces each week, and to present an original research proposal by the end of the quarter.

Grading and Required Work

Students enrolled in SYMSYS 275/BIO 175 will be expected to do the following:

Attend and participate in class sessions
Write a weekly 2-paragraph summary of each presentation (Weeks 2-8): 1 paragraph outlining the project, and 1 paragraph on future research questions (due in the discussion forum by Monday at 5pm following the previous week's presentation - 1 point off if posted after 5pm, and then 1 point off for each additional day late until 0 points are reached)

NOTE: Each week's forum thread is linked in the Schedule below as it becomes available

Do a final project proposal, including:

A written 2-page proposal (either single- or double-spaced) for a research project involving the study of collective behavior that applies methods discussed in class (due at 10pm on Wednesday, June 7)
A 5-minute oral presentation outlining the proposal, to be given on either May 31 or June 7

Grades will be assessed based on individual contributions to the class, as follows:

20% attendance
30% weekly summaries (best 6 of 7 weeks)
50% project proposal

Schedule of Class Sessions

CLASS SESSION	TOPIC	PRESENTER(S)	READINGS
Week 1 April 5	Introductions and Overview	Todd Davies (Symbolic Systems), Deborah Gordon (Biology), and Bernardo Huberman (Geballe Laboratory for Advanced Materials)
Week 2 April 12	In A Flash: Crowdsourcing Organizations, Collaboration, and Research	Michael Bernstein (Computer Science)	General background: Bigham, J. P., Bernstein, M. S., & Adar, E. (2015). Human-computer interaction and collective intelligence. Handbook of Collective Intelligence, 57. For added interest in the topic: Von Ahn, L., & Dabbish, L. (2004, April). Labeling images with a computer game. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 319-326). ACM.
Week 3 April 19	Better Than the Best: The Value of Collective Intelligence	Bernardo Huberman (Geballe Laboratory for Advanced Materials)	Watch this first: Video: Matt Ridley (2010), "When Ideas Have Sex", TEDGlobal2010 Background reading: Clearwater, S. H., Huberman, B. A., & Hogg, T. (1991). Cooperative solution of constraint satisfaction problems. Science, 254(5035), 1181. Huberman, B. A., & Wilkinson, D. M. (2010). Fluctuating Efforts and Interdependencies in Collaborative Work. Group Decision and Negotiation, 19(2), 169-191. Hogg, T., Huberman, B. A., & Williams, C. P. (1996). Phase transitions and the search problem.
Week 4 April 26	Communicative Action in Groups and Support Networks	Todd Davies (Symbolic Systems)	Background reading: Rosenschein, S. J., & Davies, T. (to appear). Coordination technology for active support networks: Context, needfinding, and design. AI & Society. Carman, K. L., et al. (2015). Effectiveness of public deliberation methods for gathering input on issues in healthcare: Results from a randomized trial. Social Science & Medicine, 133, 11-20. Davies, T., & Chandler, R. (2012). Online deliberation design: Choices, criteria, and evidence. In Nabatchi et al., eds., Democracy in motion (pp. 103-131). Oxford. Davies, T., & Shah, R. (2004). Intuitive preference aggregation: Tests of independence and consistency.
Week 5 May 3	An Engineer’s Perspective on Insect Swarms	Nick Ouellette (Civil and Environmental Engineering)	Background reading: Couzin, I. D., Krause, J., James, R., Ruxton, G. D., & Franks, N. R. (2002). Collective memory and spatial sorting in animal groups. Journal of theoretical biology, 218(1), 1-11. Kelley, D. H., & Ouellette, N. T. (2013). Emergent dynamics of laboratory insect swarms. Scientific reports, 3, 1073. Puckett, J. G., Kelley, D. H., & Ouellette, N. T. (2014). Searching for effective forces in laboratory insect swarms. Scientific reports, 4, 4766.
Week 6 May 10	Decision Making at Scale: Algorithms, Platforms, and Mechanisms	Ashish Goel (Management Science and Engineering and Computer Science)	Background reading: Dandekar, P., Goel, A., & Lee, D. T. (2013). Biased assimilation, homophily, and the dynamics of polarization. Proceedings of the National Academy of Sciences, 110(15), 5791-5796. Goel, A., & Lee, D. T. (2016, July). Towards large-scale deliberative decision-making: small groups and the importance of triads. In Proceedings of the 2016 ACM Conference on Economics and Computation (pp. 287-303). ACM.
Week 7 May 17	Centrality, Influence, and Diffusion in Networks	Matthew O. Jackson (Economics)	Background reading: Banerjee, A., Chandrasekhar, A. G., Duflo, E., & Jackson, M. O. (2013). The diffusion of microfinance. Science, 341(6144), 1236498. Banerjee, A., Chandrasekhar, A. G., Duflo, E., & Jackson, M. O. (2017). Using gossips to spread information: theory and evidence from a randomized controlled trial. MIT Department of Economics Working Paper No. 14-15.
Week 8 May 24	The Ecology of Collective Behavior in Ant Colonies	Deborah Gordon (Biology)	Background reading: Gordon, D. M. (2014). The ecology of collective behavior. PLoS Biol, 12(3), e1001805. Gordon, D. M. (2016). From division of labor to the collective behavior of social insects. Behavioral ecology and sociobiology, 70(7), 1101-1108.
Week 9 May 31	Student Project Proposals	students
Week 10 June 7	Student Project Proposals	students