Dr. Fuhua Lin International Graduate Research Workshop 2013 on Adaptivity and Personalization in...
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Tutorial on MultiAgent Virtual Worlds Dr. Fuhua Lin International Graduate Research Workshop 2013 on Adaptivity and Personalization in Informatics, March 23‐24, 2013 Edmonton, Alberta, Canada
Dr. Fuhua Lin International Graduate Research Workshop 2013 on Adaptivity and Personalization in Informatics, March 23‐24, 2013 Edmonton, Alberta, Canada
Dr. Fuhua Lin International Graduate Research Workshop 2013 on
Adaptivity and Personalization in Informatics, March 2324, 2013
Edmonton, Alberta, Canada
Slide 2
Outline Introduction Related Work The Roles of Agents
Architectural Design QuizMASter Conclusions and Future work
Slide 3
Goal of this Tutorial Discuss the basic concepts on
constructing virtual worlds with multiagent systems (MAS).
Slide 4
Virtual Worlds Virtual Worlds are 3D graphical environments
that provides more engaging and more immersive user experience can
provide more dimensions than physical environments more social
nuanced ways (in ways which are able to show slight difference that
may be difficult to notice but are fairly important ) for
people.
Slide 5
Athabasca Universitys Academic Research Centre in Second Life
AU's new ARC building was exactly replicated on the AU island to
assist with furniture placement and other occupancy decisions. A
video of this building is accessible here:
http://www.youtube.com/watch?v=pganB4_F7AQ There are avatar only in
this demo! The avatars are 3D characters controlled by the
participants.
Slide 6
Multiagent Systems MAS --- encompasses distributed
problem-solving applications, such as network management, which do
not typically involve Virtual Worlds has a focus on inter-agent
Communication. Coordination and Negotiation. COMP667 (Multiagent
Systems) of Athabasca University
Slide 7
Group Decision Making There are many settings where a
potentially large number of agents, each with its own goals and
objectives, collectively interact so as to produce a solution to
some problem. A solution that is produced under these circumstances
often reflects the tug-of-war that led to it, with each agent
trying to pull the solution in a direction that is favorable to
it.
Slide 8
Game Theory The field of game theory provides a natural
framework in which to talk about what happens in such situations,
when a collection of agents interacts strategically --- in other
words, with each trying to optimize an individual objective
function.
Autonomous Agents in Virtual Worlds Using virtual worlds as a
technique for exploring agent behavior and agent believability, or
Using agents as a way of extending virtual worlds into new
application areas, including Synthetic agents: intelligent actors
(Hayes-Roth et al. 1996), virtual actors, virtual humans, (e.g.
NPCs) Avatars (which are physical representation of human users) In
a 3D multi-user Web environments.
Slide 12
AGENTS Exist in an environment which they need to perceive
Autonomously react to changes in that environment Proactively act
to achieve goals Interact with other agents Behavior can be
emergent (often coded in a declarative language)
Belief-Desire-Intention (BDI) models a subset of the human
mind
Slide 13
Why Autonomous? The more autonomous, the more convincing to the
user and sustains the feeling of presence in a virtual world!
Slide 14
Behavior Modeling: Agents Level of Autonomy (LOA) Degree of
autonomy of virtual environments depends on the autonomy of their
components, three level of autonomy (LOA) (Thalmann, 2000): Guided:
user-guided, like avatar. Programmed: could use omniscient
approach, but inefficient. Autonomous: Have perception limitation
Prediction about the world are always fallible The potential for
reuse of agents in different virtual worlds The ability to
distribute individual agents over separate processors
Slide 15
Is Autonomy useful and appropriate for agents in virtual
worlds? Omniscient agent management soon runs into combinatorial
problems when it must track of what each agent is supported to know
and perceive.
Slide 16
NPCs Realistic non-player characters (NPCs) are essential to
making virtual environments more real for players. This is true in
video games where more believable NPCs support the story narrative
of a game, making them more immersive, more convincing. It is also
true in other areas where virtual worlds are used such as
education, increasing the effectiveness of those environments.
Slide 17
PROBLEM Non-player Character (NPC) behaviors in 3D virtual
worlds are not sophisticated enough Impacts believability and
ability to create complex scenarios Domains Video games
Education/Training virtual environments
Slide 18
SOLUTION Improved Artificial Intelligence driving NPC behavior
Machine Learning Natural Language Processing Machine Perception
(watching the user) Multi-agent Systems (MAS)
Slide 19
POSSIBLE APPROACHES Two approaches to combining an MAS with a
game engine A fully custom integrated solution A modular solution,
integrating existing components
Slide 20
Gamebots A fully custom integrated solution
Slide 21
Virtual Singapora
Slide 22
Problem in using MAS in Virtual Worlds Game AI is usually
closely coupled with other parts of the game code which makes it
hard to reuse or replace. Requires a large amount of investment in
time and resources and a high level of expertise in Agent Oriented
Software Engineering (AOSE).
Slide 23
GOAL Create an integrated framework to simplify the process of
creating agents to control NPCs in Open Wonderland Animation
Movement Environmental percepts Synchronization
Slide 24
PAST RESEARCH Gamebots/Pogamut (2002 - GameBots: A Flexible
Test Bed for Multiagent Team Research ) Commercial server (Unreal
Engine) Open source client (using Unreal scripting language as API)
Other Projects Not Java-based (C, C#) or not open source OpenSim
(C#) supports Second Life protocol
Slide 25
Agents Roles Research that has been done with virtual agents
and multi- agent systems can be leveraged to create more realistic
NPCs and purposeful communication channels among agents for
applications like game-style educational activities. Agent-
controlled- NPC Human Users Avatar
Slide 26
Our Approach Controlling NPCs with intelligent agents through
the creation of an interface between a multi-agent system to a
virtual world engine.
Slide 27
Open Wonderland Open Wonderland is a toolkit for building 3D
virtual worlds (Kaplan, J., & Yankelovich, 2011). The
architecture of the system, based entirely on open standards, is
highly modular and designed with a focus on extensibility. Kaplan,
J., & Yankelovich, N.: Open Wonderland: An Extensible Virtual
World Architecture. ;IEEE Internet Computing(2011), 38-45
Slide 28
Underlying Technologies Jason A platform for the development of
multi-agent systems Java-based open-source MAS used for creating
BDI agents that are based on the model of belief, desires,
intentions. A Java-based interpreter for an extended version of
AgentSpeak. The core code is easily extendible making it easy to
add customizations at the agent and environment level. AgentSpeak,
a Prolog derivative that is well suited to programming in AI, is
the language used to control agents. AgentSpeak is only language
that will be supported, at least initially, when it comes to agent
scripts run to control NPCs in Open Wonderland. Declarative style
--- offers a different way to script NPC behavior than the more
functional methods already available in Open Wonderland (like
JavaScript).
Slide 29
Underlying Technologies JADE Container model Agent Management
System (AMS) Directory Facilitator (DF) to facilitate the
management of agents. CArtAGo (Common ARTifact infrastructure for
AGents Open environments) Agents & Artifacts (A&A) model,
using workspaces, agents, and artifacts (exposed resources).
Implementation of Sensory abilities Applied by recording and
observing the student avatar behaviors, especially his/her gaze
direction. After all contestants enter the studio, the Host Agent
will greet each and every student, addressing his/her name with
eye-gaze directed to that student. User monitor --- tracking of
viewing angles of participants Contestant Name: Lin Data: Lin's
Look-Around behaviour during every question session Date: Fri Sep
23 22:01:48 MDT 2011 Question Number 1 Session -->Lin Did Not
Looked Around. Question Number 2 Session -->Lin Did Not Looked
Around. Question Number 3 Session -->Lin Did Not Looked Around.
Question Number 5 Session -->Lin Did Not Looked Around.
Slide 47
Principle 3: Situational Context Transformations Altering the
spatial or temporal structure of a conversation. For example, the
communication between agents and students can be optimally
configured in terms of the geographical setup of a conference room.
For example, a class of 20 students can sit directly in front of
the virtual instructor, and perceive the rest of the students as
sitting farther away.
Slide 48
Principle 3: Situational Context (Cont) Altering the flow of
rendered time in the communication session, users can implement
strategic uses of rewind and fast forward during a real-time
interaction in an attempt to increase comprehension and efficiency.
E.g. the point for providing hints
Slide 49
Scenario Participants Contestants The host The Audience Process
of a QuizMASter session The host greets the contestants The
audience will be cheering for and looking at all the contestants
simultaneously. Questions are displayed. Contestants will answer
the questions. Scores will be kept. Another video showing the
introduction of the host and the audience responses.