COMPUTABILITY AND INTRACTABILITY
Credit points: 15
When does a problem have an effective algorithmic solution? What does it mean for an algorithm to be effective? In this subject we attempt to give rigorous meaning to questions of this type and investigate some possible answers. Abstract computing machines and their role in the definitions of various notions of computational complexity will be discussed. Classes of problems such as P, NP will be defined and a number of well known problems in graph theory, algebra and applied discrete mathematics will be classified according to their computational complexity. The second half of the subject covers undecidability for decision problems: problems for which no algorithmic solution is possible. This property is found amongst problems from computing, abstract algebra, combinatorics, matrices and the theory of tilings.
FacultyFaculty of Science, Tech & Engineering
Subject Co-ordinatorMarcel Jackson
Available to Study Abroad StudentsYes
Subject year levelYear Level 4 - UG/Hons/1st Yr PG
Prerequisites MAT1DM and MAT2AAL and MAT1CLA, or any third year mathematics subject and requires co-ordinators approval
Special conditions Offered subject to sufficient enrolments.
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Melbourne, 2014, Semester 1, Day
Maximum enrolment sizeN/A
Subject Instance Co-ordinatorMarcel Jackson
Two 1.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
"requires extensive preparation for class presentations"
|Four assignments each equivalent to 700 words||60|
|One assignment equivalent to 1,100 words||40|