- •Intelligent Agents
- •1. Introduction
- •2. The eva approach
- •3. Eva Architecture Overview
- •3.1 Nano-Agent Architecture
- •3.2 The Nanocheme Language
- •3.3 Artificial Life Primitives
- •3.4 Natural Language Interaction
- •4. The Experimental Prototype
- •4.1 Believable Intelligent Agents
- •4.2 Schizophrenic mental Model
- •4.3 Emotions
- •4.4 Memory and Web Mining
- •4.5 Graphical Interface
- •5. Results
- •5.1 Eva vs. Alice
- •5.2 Discussion
- •6. Conclusion and Future Works
- •Virtual Worlds
- •1. Introduction
- •2. Related work
- •2.1 Norms in web based communities
- •2.2 Combining multiagent systems and virtual environments
- •3. Modelling activities in a social virtual world
- •3.1 Our approach: a hybrid system with software agents and humans in 3d virtual
- •3.2 An organization based Multiagent System
- •3.3 Intelligent objects to control and assist participants' activities
- •4. Generic framework to enforce norms in svw
- •4.1 General description
- •4.2 Prototype
- •5. Conclusions
- •1. Introduction
- •2. Background & Related Work
- •2.1 Background
- •2.2 Related Work
- •2.2.1 Web portal system
- •2.2.2 Service oriented architecture
- •2.2.3 Single sign-on approach
- •2.2.4 Web resources monitoring
- •2.2.5 Site map
- •3. Design Objectives & Requirements
- •4. System description & implementation
- •4.1 Overall architecture
- •4.2 Redirect scheme & Single sign on service
- •4.2.1 Redirect scheme
- •4.2.2 Single sign on service
- •4.2.2.1 Single sign on components
- •4.2.2.2 Single sign on approaches
- •4.3 Portal design & implementation
- •4.3.1 Classification of function linkages
- •4.3.2 Access control capability
- •4.3.3 Ddnm design & implementation
- •4.3.4 Content of configuration file
- •4.3.5 A case study
- •4.3.6 DdnmLog Scheme
- •4.3.7 Additional tools
- •5. Achievements & performance evaluation
- •5.1 Achievements
- •6. Discussion
- •7. Conclusion
- •1. Introduction
- •2. The a3 approach to brain informatics
- •2.1 The a3 vision on the mechanism of mind
- •2.2 Place of a3 approach among other approaches
6. Conclusion and Future Works
EVA is a long term open project for designing artificial creatures. There are many possible
and promising research directions for the near future. Some are related to the technological
development of the bio-inspired nano-agent system, while some others are related to a
deeper study of the schizophrenic model for creating rich believable characters. From the
technological perspective, we are implementing new additional “plugin” packages for more
robust web mining and memory functionalities using evolutionary programming and
swarm algorithms. Our goal is to learn information from the flow of conversation and from
the web rather than coding a large amount of predefined knowledge. We are also
implementing a C++ version of the EVA virtual machine that will enable to develop
applications that do not support the Java environment such as the iPhone or some robot
platforms. From the schizophrenic model perspective, we are studying various models
based on psychological, neurophysiological, and storytelling approaches. We also want to
experiment a larger number of personalities to create a swarm with social network
properties. While our theoretical framework is based on the complex system approach, our
experimental approach focuses on real-world applications. The EVA bio-inspired
architecture has obvious applications for designing intelligent agents for commercial web
sites and marketing studies. We also like to imagine virtual assistants on mobile phones,
assistants for lone aged and/or sick people, for learning foreign languages, virtual
characters in video games, for robotic and embedded applications.
X
Controlling and Assisting Activities in Social
Virtual Worlds
I. Rodriguez, A. Puig and M. Esteva
Applied Mathematics Department. University of Barcelona, Spain
Artificial Intelligence Research Institute. Barcelona, Spain
1. Introduction
Since its beginning, web technology has advanced from a text-based to a visual-based
interaction. This evolution has been facilitated by both high speed internet connections and
PC's graphical power. Virtual world (VW) technology began as standalone applications
(e.g.. virtual simulations) but soon evolved into web-based applications. Nowadays, home
users for entertainment and wide-spread enterprises or institutions for business can exploit
virtual worlds to develop remote activities between friends, employees, clients, teachers or
students (Sherman, 2002). Then, virtual worlds have clear applications in e-governance, elearning
and e-commerce, and therefore it is mandatory to study mechanisms ensuring the
assistance and the control of activities taking place in these applications.
We focus on social virtual worlds populated by participants that act in order to achieve
common and individual goals (Bartle, 2003). Due to the type of activities taking place in a
Social Virtual World (SVW), the virtual environment should be prepared to be a dynamic
space where participants are informed about activities' evolution and where norms are used
to organize participants' actions, to define actions' consequences and to prevent undesired
participants behaviours. We rely on electronic institutions (Esteva, 2003) to set up
participants' valid interactions and on virtual objects, named intelligent objects, populating
the virtual world, to enforce norms and to give assistance to participants (Rodriguez, 2008).
This work exploits the Virtual Institution (VI) concept which is a combination of both
multiagent and virtual world technologies (Bogdanovych, 2007).
We have designed a general framework of object behaviour control tied with an IA based
external module and prepared to be exploited by several virtual world platforms. This is
done creating a specific module to capture participant interactions on objects populating the
virtual world and connecting this module with an external and generic one in charge of
deciding what should be the virtual object action. Decision depends on an organizationbased
multiagent system (MAS) which, as said before, establishes the valid interactions
participants may have and the consequences of those interactions. Our main objectives are:
Establish participants' roles, activities and norms by means of a multiagent system
named electronic institution. Participants can be both software agents and humans.
Controlling and Assisting Activities in Social Virtual Worlds 13
2
Use of intelligent virtual objects with an external module named iObject manager i)
to inform participants about activities evolution and ii) to decide whether
participants comply established norms.
Design an object behaviour control scheme applicable to different VW (Virtual
World) platforms.
Exploit the virtual nature of the spaces, and the objects populating these spaces,
allowing to represent things impossible for their real world counterparts.
The dynamic feature of current VW platforms only rely on users who are free to
dynamically change aspects of the virtual world by means of built-in tools and scripting
features. Our proposal is to extend the ability of a VW to dynamically change itself and
exploit the virtualness of the space supporting the presentation of information, which would
be impossible to do in the real world, and so provide a better support to participants on
their activities.
This chapter is structured as follows. Section 2 presents related work in areas related with
norms enforcement in virtual worlds and multiagent systems combined with virtual
environments. Section 3 describes how our system models activities taking place in
normative virtual worlds and uses intelligent objects to guide and control the user during
the activities. Section 4 presents the developed intelligent objects framework and finally
section 5 presents conclusions and future work.