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Paul Werbicki
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CPSC 699 – Plan Two
Thesis Topic Introduction
Software agents comprise a very general and active area of research being performed in
Computer Science today. Their appeal is the satisfaction of developing software that is able to
operate autonomously in an environment to achieve a particular goal using the abilities
bestowed upon it by its creators; in essence the giving of life to one’s program. An agent’s
potential to achieve human-like interaction with its environment, including other agents, has
given a new direction to the field of Artificial Intelligence.
The environment in which an agent perceives its surroundings and is able to act upon those
perceptions is often called agent architecture. The type of architecture used depends directly
upon the problem begin analyzed. When studying human-like behavior the architecture used is
one that models the real world as closely as possible. Researchers study software agents
interacting in a virtual 3D environment in order to model how humans interact in the real
world. Agents control avatars which are able to interact with other agents, both software and
human.
It is the entertainment industry that has developed much of the current state-of-the-art in
virtual 3D environments. Much of it is based on computer game engines which represent the
latest in real-time computer graphics rendering techniques pulled together from both academic
research and industry development. The game industry is consistently pushing the boundary of
available hardware, especially when it comes to graphics processors. Computer game engines
bring together many diverse areas of Computer Science: data structures, graphics rendering,
networking, algorithm optimization and artificial intelligence. The goal is to provide the user
with a rich, immersive, engaging experience and keep them entertained for hours on end.
In the typical first-person shooter computer game, bots (robots) are used to provide the user
with an interactive experience. It is the game bots that are the agents of the virtual game world,
interacting with other game bots and humans in an endless struggle for dominance. As agents,
game bots are a very primitive attempt at programming an autonomous player. These agents
use highly specialized systems for mimicking human behavior and give the illusion of
intelligence that is required in a quick-moving game environment. However, as games are
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developed that require higher levels of sophisticated interaction; these primitive agents are
generally not up to the task.
The integration of Artificial Intelligence into the game platform has become a relatively new
research area in Computer Science over the last few years. In his often cited paper on the
integration of Artificial Intelligence and interactive computer games (Laird and van Lent, 2000)
Dr. John Laird talks about using the computer game as a platform for pursing human-level
Artificial Intelligence research. As an architecture it provides a realistic environment in which
researchers can develop software agents with cognitive capabilities able to interact physically
and socially in a setting akin to the real world.
Several research groups are actively using computer game engines to interface Artificial
Intelligence research with real-time graphics rendering. SOAR (Laird, 2003) is an architecture
used to develop agents that exhibit intelligent behavior. Used in conjunction with the Quake
game engine, researchers were able to integrate the AI engine into the architecture, thereby
allowing the agent to leverage the latest in Artificial Intelligence. Other initiatives (Manojlovich,
Chen and Lewis, 2003; Laird and Duchi, 2002) use the Unreal Tournament game engine to
achieve a similar interface into the architecture. This type of research focuses on the
intelligence portion of the agent, leaving the architecture up to the game industry.
Having the architecture driven by the game industry leaves researchers little choice as to what
information their agent is able to perceive from the architecture. How an agent perceives its
environment is an important step to providing all of the necessary information to make an
informed decision. Primitive techniques are used currently to allow agents to “see” their virtual
environment, however these methods are highly specialized based on the game design and the
purpose of the agent software.
I propose using Computer Graphic rendering techniques, such as BSP Trees, to render a 3D
environment into a data structure usable by an agent, thereby allowing it to “see” that
environment. This will provide an agent with more then simple “radar” vision. The approach
has two stages. First meta information is placed in the environment by the designer who
groups sets of polygons into higher level objects such as stairs, walls, doors, etc. This
information is compiled into the environment producing a representation of the environment
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usable by a graphics-rendering engine. Next the environment is rendered but instead of using a
graphics pipeline to display the objects to the screen, information on the visible objects, along
with their meta information, is sent for processing by the agent software.
In this fashion it is possible to develop an agent architecture that is extensive enough to be
useful for further development while at the same time generic enough to be applicable to the
development of other agent architectures and computer game engines.
Paul Werbicki
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Revised Thesis Plan
Continued research in my thesis topic has not revealed anyone working in the area of agent
vision in virtual 3D environments. An extensive search of the Internet has produced
interesting information in similar topics, however nothing directly related to my thesis work.
Many papers exist on using computer game engines to further research in Artificial Intelligence
and my next task is to delve further into these references for papers relevant to my research
topic while at the same time establishing the originality of my idea.
My thesis plan currently remains the same as before, and it is still very high level and subject to
change. As I discover related research and adjust my approach I will be able to further refine
the timeline presented here.
Winter 2003
Fall 2003
Perform initial research into various disciplines of Computer
Science in order to decide on a thesis topic.
First draft of my thesis proposal.
Attending CPSC 699 Research Methodologies course.
Final draft of my thesis proposal.
First draft of my literature survey:
 Search for existing research that may cause me to alter
the focus/goal of my thesis.
 Find primary/secondary sources in my research area.
 Contact prominent individuals who are already
performing similar research in my area.
First draft of an implementation plan for the software required
by my thesis.
January 2004
February 2004 –
May 2004
Summer 2004 –
Winter 2005
First draft of the abstract, introduction and reading survey of
my thesis.
Finalize thesis problem and goals.
Final draft of my implementation plan.
Perform readings of research on my thesis topic.
First draft of thesis without supporting software.
Continuing research in my topic area.
Implementation of software required for completion of my
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thesis.
Spring 2005
Final draft of thesis with results derived from the completion of
all required software.
Submit thesis for defense.
Paul Werbicki
[email protected]
Relevant Resources
As a graduate student there are many resources available to help in researching my thesis topic.
The most indispensable is the university library, especially the online paper and journal
databases. The public Internet does not contain the same quality of information as found in
the library’s online databases. As well the document delivery service is there should one find a
document but be unable to retrieve the full-text online.
Given that I am working on virtual 3D worlds, the topic that I am pursuing does not require
any special computer hardware or software beyond those provided by the University. Based on
the timeline of my thesis and the rapid advance of graphics technology, it may be useful to
upgrade to the latest 3D graphics accelerator in order to improve graphics rendering.
However, the goal is to use Computer Graphics only to extent required to help visualize the
agent’s environment.
Finally the research being performed at the University may provide opportunities for
collaboration. Some of the work being done by my supervisor is directly related to agent
architectures, the basis of my thesis. As well there exists a Media Lab who are affiliated with
the Concentration in Computer Game Design program. It may be possible to work with this
group on some of the graphics related portions of my topic.
Relevant Readings
Epic Games Inc. Unreal Tournament 2003 Game 2003. Accessed on 19 Oct 2003
<http://www.unrealtournament2003.com>
John
E.
Laird.
SOAR
Home
Page
2003.
Accessed
on
1
Oct
2003
<http://www.eecs.umich.edu/~soar/>
John E. Laird, et al. “A Test Bed for Developing Intelligent Synthetic Characters.” AAAI
Spring Symposium on AI and Interactive Entertainment (Mar 25-27, 2002).
John E. Laird and John C. Duchi. “Creating Human-like Synthetic Characters with Multiple
Skill Levels: A Case Study using the Soar Quakebot.” AAAI 2000 Fall Symposium Series:
Simulating Human Agents (Nov 2000).
Paul Werbicki
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John E. Laird. “Research in Human-Level AI using Computer Games.” Communications of
the
ACM
45.1
(Jan
2002):
32-35.
Accessed
on
23
Sep
2002
<http://doi.acm.org/10.1145/502269.502290>.
John E. Laird and Michael Van Lent. “Human-Level AI’s Killer Application: Interactive
Computer Games.” Proceedings of the Seventeenth National Conference on Artificial
Intelligence
(2000):
1171-1178.
Accessed
on
1
Oct
2003
<http://www.kddresearch.org/Groups/AI-CBR/Papers/Interactive-computer-gamesAIMag22-02-003.pdf>
Joseph Manojlovich, Jinlin Chen and Michael Lewis. UUTSAF: A Simulation Bridge between
OneSAF
and
the
Unreal
Game
Engine
2003.
Accessed
on
Oct
30
2003
<http://usl.sis.pitt.edu/ulab/pubs/utsaf-smc03.pdf>
Id Software Inc. Quake II 1997. Accessed on Oct 18 2003 <http://www.idsoftware.com>