Course Title: Agent-Oriented Programming and Design
Part A: Course Overview
Course Title: Agent-Oriented Programming and Design
Credit Points: 12.00
Terms
Course Code |
Campus |
Career |
School |
Learning Mode |
Teaching Period(s) |
COSC1204 |
City Campus |
Undergraduate |
140H Computer Science & Information Technology |
Face-to-Face |
Sem 2 2006, Sem 2 2007, Sem 2 2008, Sem 2 2009, Sem 2 2010, Sem 2 2011, Sem 2 2012, Sem 1 2015 |
COSC1204 |
City Campus |
Undergraduate |
171H School of Science |
Face-to-Face |
Sem 2 2018, Sem 2 2020 |
COSC2048 |
City Campus |
Postgraduate |
140H Computer Science & Information Technology |
Face-to-Face |
Sem 2 2006, Sem 2 2007, Sem 2 2008, Sem 2 2009, Sem 2 2010, Sem 2 2011, Sem 2 2012, Sem 1 2015 |
COSC2048 |
City Campus |
Postgraduate |
171H School of Science |
Face-to-Face |
Sem 2 2018, Sem 2 2020 |
Course Coordinator: Dhirendra Singh
Course Coordinator Phone: N/A
Course Coordinator Email: dhirendra.singh@rmit.edu.au
Course Coordinator Location: 14.08.7B
Course Coordinator Availability: By appointment, by email
Pre-requisite Courses and Assumed Knowledge and Capabilities
You may not enrol in this course unless it is explicitly listed in your enrolment program summary.
Enforced Prerequisite: Advanced Programming OR Programming 1 OR Programming Techniques
Assumed Knowledge: algorithms, programming, basic mathematics and statistics.
Course Description
The course provides a foundation in agent-based modelling and simulation techniques for understanding complex systems. Agent-based models (ABMs) work by representing the entities (agents) of a system and their interactions from which system-level phenomena emerge. Examples of emergent phenomena that can be represented with ABMs include flocking in birds, traffic congestion on roads, and spread of infection in a population.
In this course you will learn how to design, implement, use, analyse, and critique agent-based models of complex systems. You will construct “what-if” scenarios, and implement “policy interventions”, to examine how exogenous changes can perturb the system, and use critical analysis to determine likely impacts of proposed changes.
This is a studio-style course, with a strong emphasis on learning by doing.
Please note that if you take this course for a bachelor honours program, your overall mark in this course will be one of the course marks that will be used to calculate the weighted average mark (WAM) that will determine your award level. This applies to students who commence enrolment in a bachelor honours program from 1 January 2016 onwards. See the WAM information web page for more information.(http://www1.rmit.edu.au/browse;ID=eyj5c0mo77631)
Objectives/Learning Outcomes/Capability Development
This course contributes to the following Program Learning Outcomes in BP094 Bachelor of Computer Science and BP096 Bachelor of Software Engineering:
PLO1: Knowledge - Apply a broad and coherent set of knowledge and skills for developing user-centric computing solutions for contemporary societal challenges.
PLO2: Problem Solving - Apply systematic problem solving and decision-making methodologies to identify, design and implement computing solutions to real world problems, demonstrating the ability to work independently to self-manage processes and projects. requirements.
PLO4: Communication - Communicate effectively with diverse audiences, employing a range of communication methods in interactions.to both computing and non-computing personnel.
PLO5: Collaboration and Teamwork - Demonstrate effective teamwork and collaboration by using tools and practices to manage and meet project deliverables.
PLO6: Responsibility and Accountability - Demonstrate integrity, ethical conduct, sustainable and culturally inclusive professional standards, including First Nations knowledges and input in designing and implementing computing solutions.
The objective of this course is to develop an understanding of and gain experience with agent-based modelling and simulation concepts and technology. Upon successful completion of this course students should be able to:
- Demonstrate an understanding of agent-based modelling and simulation concepts, and be able to apply these concepts for modelling different kinds of complex systems;
- Design, implement, calibrate, and validate, agent-based models, as well as interpret and summarise their outputs;
- Use state of the art development environments to build agent-based models for practical use;
- Apply critical analysis and problem-solving skills to extend and enhance existing techniques;
- Develop skills for further self-directed learning in the general context of agent-based modelling and simulation;
- Communicate scientific knowledge effectively, in both oral and written form.
Overview of Learning Activities
This course will be delivered in “studio” mode with no formal lectures.
Each week, prior to class, you will undertake preparatory work which will include reading recommended text, watching recommended videos, and completing homework tasks. Then during class this material will be reinforced in an interactive session through discussions, presentations, quizzes, and practical hands-on application.
Throughout the semester, you will work both individually and in teams on designing and implementing agent-based models of complex systems.
Group discussions (including in online forums) focused on projects and problem solving will provide practice in the application of agent-based modelling concepts, allow exploration of concepts with teaching staff and other students, and give opportunities for receiving feedback on your progress and understanding.
Student-directed study will be fundamental in this course for consolidating your understanding of the theory and practice. You will also be expected to work collaboratively in teams for projects and presentations.
Total study hours
A total of 120 hours of study is expected during this course, comprising:
Teacher-directed hours (24 hours): Each week there will be a two hour class in “studio” mode where material will be reinforced through discussions, presentations, quizzes, and practical hands-on application.
Student-directed hours (96 hours): You will be expected to be self-directed, studying independently outside class. This will include completing study tasks each week, as well as working individually and in groups on due projects and presentations.
Overview of Learning Resources
The course will be supported via a variety of tools available online. You will be able to access course information, learning materials, and any recommended textbooks through the Canvas learning management system. Lists of relevant reference texts, resources in the library and freely accessible Internet sites will be provided.
Overview of Assessment
This course has no hurdle requirements.
The assessment for this course comprises:
Assessment Component 1: Assignment
Weighting 30%
This assessment task supports CLOs 1, 2, 3, 4
Assessment Component 2: Project
Weighting 50%
This assessment task supports CLOs 2, 3, 4, 5, 6
Assessment Component 3: Quizzes
Weighting 20%
This assessment task supports CLOs 1, 5, 6
Please note that postgraduate students are expected to demonstrate deeper knowledge and a higher level of application of knowledge and skills than undergraduate students. Assessment tasks set for postgraduate students will be different and more challenging than for undergraduate students.