COMP 2000: Collaborative and Emergent Behaviour

A grasp of computation as a significant paradigm for understanding both technology and modern models of natural phenomena, and its connection to other fields of human inquiry, is valuable for students generally. Existing courses related to computation are not generally accessible to majors in non-mathematical disciplines, and require extensive background in programming. This course is intended to be generally accessible to undergraduate students, and will be of particular interest to students in Communications Studies.

Lab In addition to classes, this course has approximately six structured laboratory session per semester.

Prerequisites: None

Availability: This course is occasionally offered, but will not be available every academic year.

Course Objectives

Collaborative and Emergent Behaviour is a survey of computation as a means of understanding, modeling, and describing artificial and natural systems. The emergence of complex behaviour from the interaction of simple rules governing individual components is illustrated and discussed, as well as the role of communication between system components. Selected systems to be studied will be drawn from different topic areas which may include the worldwide web, the mind (cognitive science), formal logic, autonomous robotics, chaos and fractals, and bioinformatics. Each topic will incorporate an associated laboratory experience.

Representative Workload
  • Topic Tests (5) 25%
  • Lab Reports (6) 25%
  • Final Exam 50%
Representative Course Outline
  • Introduction
    • Complex systems: Examples of complex systems, concepts of causality, predictability, and determinism in classical natural science, introduction to chaos, randomness, and emergence as properties of dynamical systems.
    • Communication and logic: “Real-world” reasoning versus formal logic, semantic limitations, concept of “truth” and “knowable,” communication, representation, and encoding of information.
  • Selected Topic Area: Chaos and fractals
    • Examples of self-similarity in nature and mathematics, dimensionality in fractal objects, feedback and stability of dynamical systems.
    • Lab work: Guided exploration of rules for generation of fractal objects and landscapes.
  • Selected Topic Area: Internet and Mobile Computing
    • Models of networks (client-server, peer-to-peer, and so on), web technologies and applications, protocols, layers, switching.
    • Lab Work: Use mobile devices to explore underlying functionality of network (connectivity, authentication, security).
  • Selected Topic Area: Bioinformatics
    • Function and encoding (DNA/RNA/transfer RNA), pattern matching, sequence alignment, gene regulation and metabolism.
    • Lab Work: Sequence reconstruction and pattern matching (using GENBANK).
  • Selected Topic Area: Robotics
    • Kinematics, perception, and control, swarm intelligence, communication and emergence.
    • Lab Work 1: Experiment with control parameters for a two-wheeled robot.
    • Lab Work 2: Experiment with rules for robot co-operation and group behaviour.
  • Selected Topic Area: Cognitive Science
    • Metaphors for mind, mind as computation, limits on computational minds, human problem solving, artificial intelligence.
    • Lab Work: Beat the computer at problem solving; can you pass a reverse Turing test?
  • Students will be expected to attend the six bi-weekly three-hour lab sessions and to submit a lab report at the end of each lab.

Page last updated May 24th 2021