CS2013-final-report

everyday lives, and therefore at least worth studying, if not majoring in it. The course is divided into knowledge
units. Each knowledge unit exemplifies key concepts that are associated with the scientific method, including
Problem definition, Hypothesis generation, Experiment design and implementation, Results analysis, Model design,
and Model validation and verification.
The knowledge units address issues of everyday interest to the general population. Knowledge units have included:
movement of ants, economics, spread of epidemics, climate change and global warming, cancer, predator-prey
relationships, cooperation and collaboration, computer games, arts and music, fractals, and metabolism of lactose
(lac operon). In addition, students are exposed to tools, methods, theories, and paradigms that allow them to consider
patterns that transcend application domains and problems. These methods and tools include the science of
complexity, the science of networks, fractals, chaos theory, problem solving techniques, and game theory.
Because of the diversity in the majors of students who take this course (Business, Computing, Engineering, Liberal
Arts, etc.) and the diversity of topics that are covered, some students find this course challenging while others feel it
is less so. Again, our goal is to make the course relevant, interesting, and applicable to current issues.
Body of Knowledge coverage
KA Knowledge Unit Topics Covered Hours
CN Fundamentals Models as abstractions of situations 3
CN
Modeling and
Simulation
Purpose of modeling and simulation including optimization; supporting decision
making, forecasting, safety considerations; for training and education.
Important application areas including health care and diagnostics, economics and
finance, city and urban planning, science, and engineering.
3
.
CN
Modeling and
Simulation
Model building: use of mathematical formula or equation, graphs, constraints;
methodologies and techniques; use of time stepping for dynamic systems.
.
15
CN
Modeling and
Simulation
Formal models and modeling techniques: mathematical descriptions involving
simplifying assumptions and avoiding detail. The descriptions use fundamental
mathematical concepts such as set and function. Random numbers.
3
CN
Modeling and
Simulation
Assessing and evaluating models and simulations in a variety of contexts;
verification and validation of models and simulations.
18
IS Agents Multi-agent systems
Collaborating agents
Agent teams
Competitive agents (e.g., auctions, voting)
Swarm systems and biologically inspired models
15
Other KA’s are covered in other courses
n/a
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