• Instructor: Alan Mackworth
• Classes: Tuesday & Thursday, 11:00-12:20, ICCS 104
  
• First Class: Tuesday, January 7, 2014
• Last Class: Tuesday, April 8, 2014
  
• Office hours: Tuesday 14:00 - 14:30, or by appointment, ICCS 121
• Website: ComputationalSustainabilityCourse
• Overview(.pdf): ComputationalSustainabilityCourseOverview
• Student Service Centre: CPSC 530M
• Forum for discussions, postings and grades: connect.ubc.ca
  

Computational Sustainability

Computational sustainability is an emerging interdisciplinary field that applies computational techniques from computer and information science, operations research, applied mathematics and statistics to facilitate the integration of environmental, societal and economic needs and constraints for sustainable development.

Themes

1. Development of computational models and methods for decision-making to facilitate management and allocation of social, economic and environmental costs and benefits.
2. Development of in-the-loop embedded computational modules for monitoring, management and control of ecological, technical and social systems.
3. Study of the impact of the deployment of information and communication technologies (ICT) on sustainability.

The course is designed to be an introduction to computational sustainability, providing a broad coverage of the field. It is suitable for graduate students in computer science and computer engineering or graduate students in other disciplines with good familiarity with algorithms and computational methods.

Image source: (Poole & Mackworth, 2010)

Framework

• The unifying framework is constraint-based sustainability; constraint satisfaction is at the core.
• Sustainable systems must satisfy various physical, chemical, biological, psychological, social and economic constraints.
• Such constraints include energy supply, waste management, GHG, ocean acidity, climate, ecological footprint, biodiversity, habitat, harvesting, global equity, ....
• Planetary boundaries define the safe operating region in the multidimensional state space of the evolving planetary system.
• The computational tools used include dynamical systems, simulation, control theory, constrained optimization, machine learning, artificial intelligence, software engineering, information visualization, human-computer/robot interaction, game theory and mechanism design.
  
• The design space for computational sustainability systems has five dimensions: 
1. Level: Primary level that constraints operate at: biophysical, biological, social or economic. Most systems operate with constraints at several levels.
2. Domain: Application sphere: climate, ocean, energy, agriculture, transportation, urban design, education, healthcare, ...
3. Type:   model or embedded (in-the-loop)
   
4. Spatial Scale: From nano (10-9m) to global (107m)
5. Temporal Scale: From fast (10-3s) to slow (109s)
• We shall explore the design space by studying a variety of application case studies such as climate change, oceanographic modeling, wildlife corridor design, social life of zebras, energy management, smart buildings, self-driving cars, urban design, wheelchair mobility, aging and technology, crop disease monitoring, livestock insurance, rural agricultural market design, and mobile phones and social change.
  

Organization

• The classes will be organized around talks, readings and seminar discussions led by the instructor, the students and guest lecturers.
• Each student will complete a project, as described here.
  

Resources

Schedule, Topics and Readings

Here is the Class Schedule with the weekly topics and readings.

Grades

Student grades will be based on class participation (20%), project proposal (10%), project presentation (20%) and the final project paper (50%). There will be no exams in the course.