- author = "Swen E. Gaudl",
- title = "Building Robust Real-Time Game AI:Simplifying \& Automating Integral Process Steps in Multi-Platform Design",
- school = "University of Bath",
- year = "2016",
- address = "UK",
- keywords = "genetic algorithms, genetic programming, games,digital games, agent design, agent programming language, software development, artificial intelligence",
- idcode = "53314",
-
URL = "
http://opus.bath.ac.uk/53314/1/dissertationRoot.pdf",
-
URL = "
http://opus.bath.ac.uk/53314/",
-
URL = "http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.698997",
- size = "265 pages",
-
abstract = "Digital games are part of our culture and have gained
significant attention over the last decade. The growing
capabilities of home computers, gaming consoles and
mobile phones allow current games to visualise 3D
virtual worlds, photo-realistic characters and the
inclusion of complex physical simulations. The growing
computational power of those devices enables the usage
of complex algorithms while visualising data.
Therefore, opportunities arise for developers of
interactive products such as digital games which
introduce new, challenging and exciting elements to the
next generation of highly interactive software systems.
Two of those challenges, which current systems do not
address adequately, are design support for creating
Intelligent Virtual Agents and more believable
non-player characters for immersive game-play. We start
in this thesis by addressing the agent design support
first and then extend the research, addressing the
second challenge. The main contributions of this thesis
are:
The POSH-SHARP system is a framework for the development of game agents. The platform is modular, extendible, offers multi-platform support and advanced software development features such as behaviour inspection and behaviour versioning. The framework additionally integrates an advanced information exchange mechanism supporting loose behaviour coupling.
The Agile behaviour design methodology integrates agile software development and agent design. To guide users, the approach presents a work-flow for agent design and guiding heuristics for their development.
The action selection augmentation ERGo introduces a white-box solution to altering existing agent frameworks, making their agents less deterministic. It augments selected behaviours with a bio-mimetic memory to track and adjust their activation over time. With the new approach to agent design, the development of deepagent behaviour for digital adversaries and advanced tools supporting their design is given. Such mechanisms should enable developers to build robust non-player characters that act more human-like in an efficient and robust manner. Within this thesis, different strategies are identified to support the design of agents in a more robust manner and to guide developers. These discussed mechanisms are then evolved to develop and design Intelligent Virtual Agents. Because humans are still the best measurement for human-likeness, the evolutionary cycle involves feedback given by human players.",
-
notes = "BOD using POSH, FAtiMA, ABL, StarCraft,
posh-sharp
ISNI: 0000 0004 5993 9610 uk.bl.ethos.698997 supervisor Joanna J. Bryson
also known as \cite{bath53314}",
