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Module Descriptor School of Computer Science and Statistics

Module CodeCS7056
Module NameAutonomous Agents
Module Short Title
Semester Taught
Contact Hours

3 Lectures, 1 Lab per week

Module PersonnelDr Mads Haahr
Learning Outcomes

On successful completion of this module students will be able to:

  • Develop computer-controlled characters that are aware of their environment, can react to external stimuli and can behave according to sets of rules defined by a game designer
  • Represent knowledge and learning for the purposes of real-time simulations
  • Develop systems that allow procedural generation of basic stories, drama and character emotions
Learning Aims

This module aims to give students the theoretical and practical knowledge to build systems that can drive agent behaviour in games.  A variety of different approaches are covered, from methods based on academic AI to industry-developed techniques used in top selling titles.

Module Content

Themes addressed within the module include:

  • Game AI overview and objectives
  • Reactive Agents & Simulation
  • Finite State Machines (FSM) and State-Driven Agent Design
  • Path finding and optimisation problems
  • Scripting agent behaviour
  • Emergent behaviour systems
  • Opinion systems
  • Automated story and drama generation
  • Representing emotion in games
Recommended Reading List
  • Programming Game AI by Example. Mat Buckland. Wordware Publishing, 2005.
  • AI Programming Wisdom 1 – 3 (Game Programming Series), Steve Rabin (Ed.).
  • Artificial Intelligence for Games, 2nd Ed.  Ian Millington.  CRC Press, 2009.
Module Prerequisites

Java/C++/C# software development. Algorithms and data structures. Scripting languages and finite state machine systems.

Assessment Details

The course will be assessed solely on the basis of coursework. If required to repeat a student will be assigned a coursework project which they will be required to pass.  A passing grade in all cases is 50%.

Module Website
Academic Year of Data