Autonomous agents, social systems and the new cognitive science

Posgrado en Ciencia e Ingeniería de la Computación

Plan: Maestría en Ciencia e Ingeniería de la Computación (Clave 80-4014)
Actividad académica: Temas Selectos de Inteligencia Artificial
Tema: Agentes Autónomos, Sistemas Sociales, y la Nueva Ciencia Cognitiva

Horarios: Martes y Jueves, 14:30 – 16:00 (Primera clase: 27 de enero)
Lugar: Sala 203, 2do piso, anexo del IIMAS, Circuito Escolar, Ciudad Universitaria, DF

In this new course Dr. Tom Froese (IIMAS, C3) will introduce ongoing debates in cognitive science about our changing understanding of the mind. Instead of being thought of as a digital computer inside the brain, mind is now widely considered to be an embodied, embedded and extended activity in the world. These ideas will be illustrated based on case studies of research in agent-based models and human-computer interfaces, with special emphasis on demonstrating how social interactions and technologies shape our mind. Students are not expected to program models nor to design interfaces, but to understand the implications of the new cognitive science and to apply them to their own research interests. The course will be taught mainly in English to better prepare students for the special terms used by leading researchers in cognitive science.

Download the detailed program of activities here

For more information, contact Dr. Tom Froese via e-mail at t.froese AT unam.mx


Unit 1

Week 1

Lecture 1: The topic and structure of the course will be introduced.

Download slides from lecture 1

To read before next class:

Bird, J. & Di Paolo, E. A. (2008). Gordon Pask and his maverick machines. In: Husbands, P., Holland, O. & Wheeler, M. (eds.), The Mechanical Mind in History (pp. 185–211). Cambridge, MA: The MIT Press.

Boden, M. (2006/2007). Grey Walter’s anticipatory tortoises. Rutherford Journal, vol. 2.

Pickering, A. (2002). Cybernetics and the mangle: Ashby, Beer and Pask. Social Studies of Science, 32: 413-437

Lecture 2: Cybernetics

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To read before next class:

Di Paolo, E. A. (2010). Robotics inspired in the organism. Intellectica, 1-2(53-54): 129–162.

Optional:

Rosenblueth, A., Wiener, N. & Bigelow, J. (1943). Behavior, purpose and teleology. Philosophy of Science, 10(1): 18-24


Week 2

Lecture 3: Robotics

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To read before next class:

Di Paolo, E. A. (2015). El enactivismo y la naturalización de la mente. In D. Pérez Chico & M. G. Bedia (Eds.), Nueva Ciencia Cognitiva: Hacia una Teoría Integral de la Mente (in press). Zaragoza: PUZ

Optional:

van Gelder, T. & Port, R. F. (1995). It’s about time: An overview of the dynamical approach to cognition. In: R. F. Port & T. van Gelder (eds.), Mind as Motion: Explorations in the Dynamics of Cognition (pp. 1-43). Cambridge, MA: MIT Press.

Lecture 4: Cognitive science

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To read before next class: same as last class.


Unit 2:

Week 3

Lecture 5: Biology of cognition

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To read before next class: Harvey, I., Di Paolo, E., Wood, R. and Quinn, M. (2005). Evolutionary robotics: A new scientific tool for studying cognition. Artificial Life, 11: 79-98

Lecture 6: Evolutionary robotics

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To start reading: Froese, T. & Ziemke, T. (2009). Enactive Artificial Intelligence: Investigating the systemic organization of life and mind. Artificial Intelligence, 173(3-4): 466-500

Week 4

Lecture 7: Minimal cognition

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Homework: finish reading the paper by Froese and Ziemke (2009), especially the examples at the end of the article.

Lecture 8: Enactive AI

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Homework: prepare a question about the first part of the course.


Unit 3:

Week 5

Lecture 9: First assignment

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Lecture 10: Sensory substitution

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Homework: start reading the following article

Froese, T., McGann, M., Bigge, W., Spiers, A. & Seth, A. K. (2012). The Enactive Torch: A new tool for the science of perception. IEEE Transactions on Haptics, 5(4): 365-375

Week 6

Lecture 11: Tool-based transformations

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Lecture 12: The Enactive Torch

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Homework: start reading the following article (finish by end of next week)

Froese, T. & Gallagher, S. (2012). Getting interaction theory (IT) together: Integrating developmental, phenomenological, enactive, and dynamical approaches to social interaction. Interaction Studies, 13(3): 436-468


Unit 4

Week 7

Lecture 13: Social cognition

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Homework: continue reading

Lecture 14: Developmental psychology

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Homework: Start reading the following chapter:

De Jaegher, H. (2014). Enacción y autonomía: Cómo el mundo social cobra sentido mediante la participación. In A. Casado da Rocha (Ed.), Autonomía con otros: Ensayos sobre Bioética (pp. 111-131). Madrid: Plaza y Valdés

Week 8

Lecture 15: Direct perception

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Homework: continue reading; first essay due on March 18!

Lecture 16: Participatory sense-making

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Homework: start reading the following article, especially about the model:

Froese, T., & Fuchs, T. (2012). The extended body: A case study in the neurophenomenology of social interaction. Phenomenology and the Cognitive Sciences, 11(2), 205-235


Unit 5

Week 9

Lecture 17: Social contingency

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Homework:

Froese, T., Gershenson, C. & Rosenblueth, D. A. (2013).
The dynamically extended mind: A minimal modeling case study. 2013 IEEE Congress on Evolutionary Computation (pp. 1419-1426), IEEE Press.

Lecture 18: Reading break (no class)

Week 10

Lecture 19: The dynamically extended mind

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Homework:

Auvray, M., & Rohde, M. (2012). Perceptual crossing: The simplest online paradigm. Frontiers in Human Neuroscience, 6(181). doi: 10.3389/fnhum.2012.00181

Lecture 20: Perceptual crossing

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Unit 6

Week 11

Lecture 21: Modeling perceptual crossing

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Lecture 22: The social brain hypothesis

Guest seminar by Dr. Carlos Gershenson

Week 12

Lecture 23: General discussion

Lecture 24: Experiencing perceptual crossing

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Homework: Froese, T., Lenay, C., & Ikegami, T. (2012). Imitation by social interaction? Analysis of a minimal agent-based model of the correspondence problem. Frontiers in Human Neuroscience, 6(202), doi: 10.3389/fnhum.2012.00202

Week 13

Lecture 25: Modeling imitation by interaction

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Homework: take a look at the following two papers

Froese, T., Gershenson, C., & Manzanilla, L. R. (2014). Can government be self-organized? A mathematical model of the collective social organization of ancient Teotihuacan, Central Mexico. PLoS ONE, 9(10), e109966. doi: 10.1371/journal.pone.0109966

Woodward, A., Froese, T., & Ikegami, T. (in press). Occasional alteration of normal brain function can enhance global neural coordination: A spiking neural network model. Neural Networks.

Lecture 26: Modeling collective action

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Homework: prepare student presentations!