FIT4010 Advanced topics in algorithms and discrete structures - Semester 1, 2013

Algorithms are the most fundamental area for all aspects of computer science and software engineering. Discrete structures, such as those treated in graph theory, set theory, combinatorics and symbolic logic form the mathematical underpinning of the study of algorithms. As well-designed algorithms and data structures are essential for the good performance of an information system, an in-depth understanding of the theoretical properties of algorithms is essential for any computer scientist. As importantly, the theoretical investigation of algorithms leads to a deeper understanding of problem structures and classes of problems and the knowledge of a large variety of algorithm types enables the designer to approach a new problem from different angles. Topics for this unit include: Computability and Complexity Automata Theory Advanced Analysis and Design of Algorithms Parallel and Distributed Algorithms Numerical Algorithms Cryptographic algorithms Spatial/geometric algorithms

Mode of Delivery

Contact Hours

2 hrs lectures/wk, 1 hr laboratory or tutorial/wk

Workload requirements

Students will be expected to spend a total of 12 hours per week during semester on this unit as follows:

• two hour lecture and
• one hour tutorial (or laboratory) (requiring advance preparation)
• a minimum of 3 hours of personal study per one hour of contact time in order to satisfy the reading and assignment expectations.

Unit Relationships

Prerequisites

Completion of the Bachelor of Computer Science or equivalent to the entry requirements for the Honours program. Students must also have enrolment approval from the Honours Coordinator.

Chief Examiner

Campus Lecturer

Academic Overview

Learning Outcomes

• an improved understanding of the issues involved in designing algorithms in the chosen specialisation area(s) and in analysing their performance;
• an understanding of the mathematical formalisms that are relevant for these algorithms;
• learned to recognise tasks that can be solved with these algorithms;
• the ability to judge the limitations of these methods.With successful completion of the unit the students;
• the ability to choose and apply algorithms and data structures in the chosen specialisation area(s);
• the ability to evaluate the performance of algorithms using formal approaches;
• the ability to design modified algorithms in the chosen area to suit particular problem structures.

Unit Schedule

*Unit Schedule details will be maintained and communicated to you via your learning system.

Assessment Summary

Assignment and Examination, relative weight depending on topic composition. When no exam is given students will be expected to demonstrate their knowledge by solving practical problems and maybe required to give an oral report.

Teaching Approach

Assessment Requirements

Assessment Policy

Faculty Policy - Unit Assessment Hurdles (http://www.infotech.monash.edu.au/resources/staff/edgov/policies/assessment-examinations/unit-assessment-hurdles.html)

Academic Integrity - Please see the Demystifying Citing and Referencing tutorial at http://lib.monash.edu/tutorials/citing/

Assessment Tasks

Participation

Students are expected to attend lectures and tutorials. However this is not mandatory.

• Assessment task 1

  Title:

  Assignment 1 - Modelling with MiniZinc

  Description:

  In this assignment students will model a relatively simple constrained optimization problem using MiniZinc. They will be rquired to create models that work with a variety of different underlying solving techniques: MIP, CP and SAT.
  
  They will need to construct test data and then evaluate their models with this data.
  
  Produce a written report that describes their models, test data and the results of the evaluation. The report should also try and explain reasons for differences in behaviour of these models.

  Weighting:

  50%

  Criteria for assessment:

  The quality of the models: correctness, efficiency, clarity and documentation.

  The quality of the test data: coverage.

  The quality of the written report including the quality of the evaluation and analysis of the differences in behaviour.

  Due date:

  29 April 2013

• Assessment task 2

  Title:

  Assignment 2 - Building an Automated Planning system using SAT, Heuristic Search and/or NLP techniques

  Description:

  In this assignment students will investigate certain planning domains from the International Planning Competition. They will build a system to encode planning problems from that domain into SAT, Heuristic Search and / or non-linear programming formulations, which can then be solved using the aforementioned techniques.
  
  Students will need to show that their system works as desired (can discover reasonable plans) on a number of different problems (of increasing difficulty) from the chosen domain.
  
  Students will need to produce a written report describing their system and their evaluation of it.

  Weighting:

  50%

  Criteria for assessment:

  The quality of the planning system: its ability to find reasonable plans, its speed, and the type (complexity) of problems it can deal with.
  
  The quality of the written report including the quality of the evaluation and analysis.

  Due date:

  10 June 2013

Learning resources

Reading list

There are several recommended books for this subject:

• Introduction to Mathematical Programming. W. L.  Winston. Duxbury Press, 1995.
• Introduction to Operations Research. F.S. Hillier and G.J. Lieberman. McGraw-Hill, 8th Ed, 2005.
• Constraint Programming - An Introduction. K. Marriott and P. Stuckey. MIT Press, 1998.
• Numerical Optimization. J. Nocedal & S. Wright. Springer, 2006.
• Automated Planning: Theory and Practice. D. Nau, M. Ghallab and P. Traverso. Morgan Kaufmann 2004.

In addition to this, selected research papers will be referenced throughout the unit.
The lecture material will be loosely based on this material and will be available through Moodle.

Feedback to you

• Informal feedback on progress in labs/tutes
• Graded assignments with comments
• Solutions to tutes, labs and assignments

Extensions and penalties

Returning assignments

Resubmission of assignments

Resubmission is not allowed unless special consideration applies in which case the course leaders may allow the student to resubmit an assignment.

Assignment submission

Online submission

If Electronic Submission has been approved for your unit, please submit your work via the learning system for this unit, which you can access via links in the my.monash portal.

Required Resources

You will be using the MiniZinc modelling language.

This is available from: http://www.g12.csse.unimelb.edu.au/minizinc/

Other Information

Policies

Graduate Attributes Policy

Student services

Monash University Library

Disability Liaison Unit

Your feedback to Us

Previous Student Evaluations of this Unit

The changes we made last year worked well and we received a high student evaluation. We plan to update the material slightly to reflect advances in the field.