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# COMP3004 - Computational Complexity

This database contains 2017-18 versions of the syllabuses. For current versions please see here.

Code COMP3004 3 1002, 1004 and 2008 1 Fabio Zanasi (50%) Robin Hirsch (50%) To address the theoretical and practical limitations of computation. To provide a theoretical framework for modelling computation. The concepts of undecidability and intractability are introduced through a number of examples. The course will convey the proof techniques that are used to classify problems and it is intended that students learn how to apply them in order to classify unfamiliar problems for themselves. To be able to: analyse the complexity of a variety of problems and algorithms; reduce one problem to another; prove that a problem is undecidable; find a polynomial time reduction from one problem to another; determine the complexity class of a decidable problem; categorise the complexity of a language.

# Content

Models of Computation
Deterministic Turing machines.
Equivalent Turing machines.
Register machines.

Languages
Language recognition.
Language acceptance.
Recursive languages.
Recursively enumerable languages.

Undecidability
The Halting Problem.
Problem reduction.
Undecidability of the tiling problem.
Undecidability of first-order logic.
Other unsolvable problems.

Non-determinism
Non-deterministic Turing machines.
Polynomial-time reduction.
Elementary properties of polynomial time reduction.
The complexity classes P, NP, NP-complete.
Cook's theorem.
How to prove NP-hardness of various problems.

Probabilistic Algorithms
Examples of probabilistic algorithms.
How to make 'almost sure' your algorithm is correct.
Complexity analysis of probabilistic algorithms.
The complexity classes PP and BPP.

Other Complexity Classes
Space complexity.
Savitch’s theorem.
Exponential time.
Non-elementary problems.

# Method of Instruction

Lecture presentations with associated courseworks.

# Assessment

The course has the following assessment components:

• Written Examination (2.5 hours, 95%);
• Coursework Section (2 pieces, 5%).

To pass this course, students must:

• Obtain an overall pass mark of 40% for all components combined;
• Obtain a minimum mark of 30% in each component worth ? 30% of the module as a whole.

# Resources

Reading list available via the UCL Library catalogue.