SSIE - 483/583: Evolutionary Systems and Biologically Inspired Computing

Description: 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 are used to produce computational 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 are introduced to fundamental topics in evolutionary systems and bio-inspired computing, and build up their proficiency in the application of various algorithms in real-world problems.

Lecture Outline

• 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
• Automata Networks
• Development and Morphogenesis
• What is Computation?
• What is so cool about computation?
• Universal Computation and Life
• Life as Evolution of Turing Machines
• Von Neumann, Self-Replication and Open-ended evolution
• Evolution and Adaptation
• Biology through the lens of computer science
• Genetic and Evolutionary Algorithms
• Genetic Programming
• Evolutionary Robotics and Synthetic Biology
• Learning
• Neurocomputing
• Learning and evolution
• Collective Behavior and Swarm Intelligence
• Social Insects, Stigmergy and Swarm Intelligence
• Communication and Multi-Agent simulation
• Collective Computation and the Extended Mind
• Immunocomputing
• A distributed design for computational intelligence
• Multi-level complexity
• Engineering Applications
• Discussion Topics
• Evolutionary robots and embodied cognition
• Viral evolution and epidemics
• Bio-inspired Hardware
• Bio-inspired design and problem-solving
• Inferring Bio-Networks
• Whole organism modeling
• Biomolecular Self-Assembly
• DNA Computation
• Quantum Computation
• Synthetic Biology

• Participation: 15%.
• Based upon attendance and participation.
• Lab Assignments: 35% (ISE483) or 25% (SSIE583)
• Students complete 5 (best 4 graded) assignments using algorithms introduced in class.
• SSIE583 - Paper Presentation: 25%
• SSIE583 students will present and discuss a paper in class. Presentation of research paper plus leading of discussion. Students are assigned to papers as lead discussants, but all students are supposed to read and participate in discussion of every paper. During class, a lead discussant prepares a short summary of the paper (15 minutes). The summary should: 1) Identify the key goals of the paper (not go in detail over every section); 2) What discussant liked and did not like; 3) What authors achieved and did not; 4) Any other relevant connections to other class readings and beyond. After summary, discussion is opened to all, and role of lead discussant is to lead the discussion to make sure we address the important paper contributions. Also, discussant should prepare 2-3 discussion questions.
• Project or Paper: 50% (ISE483) or 35% (SSIE583)
• Students are expected to continuously consult with the instructor regarding the scope and depth of the project paper. Reusing and expanding labs is highly encouraged.

Luis Rocha: Wednesdays 9 - 12am, Engineering Building C3 (Complex Adaptive Systems and Computational Intelligence Lab) or Online, or by appointment

Samer Abubaker: Tuesday: 3:00 pm- 4:00 pm, Wednesday: 12:00 pm- 3:00 pm, and Thursday: 2:00 pm- 3:00 pm, Engineering Building EB K1. Also available for onlinemeetings .