I485/H400: Biologically Inspired Computing
Associate Instructor: Santosh Manicka.
Biological organisms cope with the demands of their environments using solutions quite unlike the traditional human-engineered approaches to problem solving. Biological systems tend to be adaptive, reactive, and distributed. Bio-inspired computing is a field devoted to tackling complex problems using computational methods modeled after design principles encountered in nature. This course is strongly grounded on the foundations of complex systems and theoretical biology. It aims to provide an understanding of the distributed architectures of natural complex systems, and how those can be used to produce informatics tools with enhanced robustness, scalability, flexibility and which can interface more effectively with humans. It is a multi-disciplinary field strongly based on biology, complexity, computer science, informatics, cognitive science, robotics, and cybernetics.
Aims: Students will be introduced to fundamental topics in bio-inspired computing, and build up their proficiency in the application of various algorithms in real-world problems.
Pre-requisites: INFO-I 211, or CSCI-C 212, or CSCI-H 212, or Instructor approval.
- What is Life?
- What is so cool about life?
- Life and Information
- The Logical Mechanisms of Life
- Imitation of Life
- Computational Beauty of Nature
- Self-similarity: fractals, L-systems, chaos
- Life as (Self-)Organization
- Artificial Life, Complex Systems and Complex Networks
- Self-Organization and Emergent Complex Behavior
- Cellular Automata
- Boolean Networks
- Development and Morphogenesis
- What is Computation?
- What is so cool about computation?
- Universal Computation and Life
- Life as Evolution of Turing Machines
- Von Neuman, Self-Replication and Open-ended evolution
- Evolution and Adaptation
- Biology through the lens of computer science
- Genetic and Evolutionary Algorithms
- Genetic Programming
- Evolutionary Robotics
- Collective Behavior and Swarm Intelligence
- Social Insects, Stigmergy and Swarm Intelligence
- Communication and Multi-Agent simulation
- Collective Computation and the Extended Mind
- A distributed design for computational intelligence
- Multi-level complexity
- Engineering Applications
- Participation: 15%.
- Based upon attendance and participation.
- Lab Assignments: 35%
- I485 (H400) students will complete 4 (5) assignments using algorithms introduced in class.
- Project: 50%
- Students will tackle a real problem using bio-inspired algorithms. Students are expected to continuously consult with the instructor regarding the scope and depth of the project.
- Luis Rocha
- Tuesdays: 10am – 12pm, Informatics East, 919 10th Street, Room #301
- Santosh Manicka
- Tuesdays and Fridays: 1-2pm, Informatics West, 901, 10th Street, Undergraduate annexe.
- Lecture notes
- Lecture slides
- Printed Resources in OnCourse
- Class Readings
- Dennet, D.C. . "Show me the Science". New York Times, August 28, 2005
- Gleick, J. . The Information: A History, a Theory, a Flood. Random House. Chapter 8.
- Kanehisa, M. . Post-genome Informatics. Oxford University Press. Chapter 1, Blueprint of life, pp. 1-23.
- Polt, R. . "Anything but Human". New York Times, August 5, 2012
- More to be added as class progresses
- Class Book
- Nunes de Castro, Leandro . Fundamentals of Natural Computing: Basic Concepts, Algorithms, and Applications. Chapman & Hall. On half.com. On Amazon.com. On Google Books.
- Recommended and Alternative Books
- Flake, G. W. . The Computational Beauty of Nature: Computer Explorations of Fractals, Complex Systems, and Adaptation. MIT Press. Available in electronic format free of charge for IU students at MIT CogNet Via the IU library.
- Floreano, D. and C. Mattiussi . Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies. MIT Press. Available in electronic format free of charge for IU students.
- Gleick, J. . The Information: A History, a Theory, a Flood. Random House.
- Mitchell, M. . Complexity: A Guided Tour. Oxford University Press. Available in electronic format free of charge for IU students.
- Mitchell, M. . An Introduction to Genetic Algorithms. MIT Press. Available in electronic format free of charge for IU students at 24x7 books Via the IU library or MIT CogNet
- Nunes de Castro, Leandro and Fernando J. Von Zuben . Recent Developments in Biologically Inspired Computing. MIT Press. Available in electronic format free of charge for IU students at 24x7 books Via the IU library.