Catalogue of Modules, University of Nottingham

G52PSA Planning, Search and Artificial Intelligence Programming
(Last Updated:03 May 2017)

Year  15/16

Total Credits: 20

Level: Level 2

Target Students:  Part I undergraduate students in the School of Computer Science. Also available to students from other Schools with the agreement of the module convenor.

This module is part of the AI, Modelling and Optimisation theme in the School of Computer Science.   Available to JYA/Erasmus students.

Taught Semesters:

Full Year Assessed by end of Spring Semester 

Prerequisites: G51IAI Introduction to Artificial Intelligence (up to 2014-15)

Corequisites:  None.

Summary of Content:  You’ll be introduced to Artificial Intelligence (AI) algorithms and programming techniques for search and planning. Topics covered include: classical search; search with non-determinism and partial observability; local search; classical planning, reasoning about actions; planning under uncertainty; conditional planning; planning with time and resources; other typical AI problems and how to implement them in an AI programming language. You’ll spend around three hours per week in lectures and computer classes studying for this module.

Method and Frequency of Class:

ActivityNumber Of WeeksNumber of sessionsDuration of a session
Lecture 23 weeks2 per week1 hour
Computing 23 weeks1 per week1 hour

Activities may take place every teaching week of the Semester or only in specified weeks. It is usually specified above if an activity only takes place in some weeks of a Semester

Method of Assessment: 

Assessment TypeWeightRequirements
Exam 1 75 2 hr written examination 
Coursework 1 25 Individual coursework 

Dr N Alechina
Dr B Logan

Education Aims:  To allow students to understand and be able to implement AI search and planning algorithms and develop new analysis, design and programming skills appropriate to AI problems.

Learning Outcomes:  Knowledge and Understanding:
Understanding and experience of AI planning and search algorithms and AI programming techniques.

Intellectual Skills:
The ability to analyse algorithms.
Enhanced program analysis and design skills.

Professional Skills:
The ability to evaluate AI algorithms and select those appropriate to a given situation and program them.

Transferable Skills:
The ability to solve problems.
The ability to retrieve information from appropriate sources.

Offering School:  Computer Science

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