Combining multiagent systems and virtual environments

A system that incorporated intelligent agents within virtual environments was mVITAL

(multi-agent VITAL) which allowed the definition of agent societies so that intelligent

agents could communicate through simple speech acts, co-operate and help each other to

achieve goals (Vosinakis et al., 1999) (Anastassakis et al. 2001a) (Anastassakis et al. 2001b) .

The mVITAL viewer allowed human supervisors to observe the activity inside the

environment. We propose to allow the user not only to supervise but to control his avatar

and communicate with a regulated multi-agent system in order to test whether his actions

are allowed. We have used the so-called iObjects in order to provide facilities for avatarobject

interaction and the visualization of the social virtual world execution context. A detail

description of iObjects integration at MAS level by means of an Interaction Language can be

found in (Rodriguez et al. 2007).

Several researches integrated BDI (Belief, Desire and Intention) agents within virtual worlds.

Torres et al. developed an interface that allowed a BDI-based agent reasoning system to be

used for guiding the behaviour of articulated characters in a virtual environment (Torres et

al., 2003). ACE (Agent Common Environment) was designed for virtual human agent

simulations. It provided pre-built commands to perceive and actuate meanwhile the

reasoning processing is defined by means of a collection of external modules (i.e. python

scripts)(Kallmann et al, 1998), (Kallmann et al, 2000). Virtual agents were used to enhance

Customer Relationship Management (CRM). eGain's virtual assistants interact in plain

English over the Web with online users (Osterfelt, 2001). They combined 3D graphical

Controlling and Assisting Activities in Social Virtual Worlds 15

representations and artificial intelligence to assist customers to locate information or place

orders. Our system provides assistance to the participant also by means of 3D graphical

representations (i.e. iObjects). An iObject allows the user to be aware of current execution

state (e.g.. data visualized on an intelligent noticeboard), enforcing norms (e.g. let to pass

through a door depending on user previous activities) and adapting object's features

depending on user profile (e.g.. adapts the font's size of a noticeboard depending on user's

visual capacity).

Guyot and Honiden's approach merged multiagent systems and role-playing games

(MAS/RPG) (Guyot, 2006). They compared agent-based participatory simulations and the

MAS/RPG approach and explained the advantages of their approach: ''actions and

interactions can be registered and used for learning purposes, the gap between the agent

model and the participants can be decreased and the user interface with an assistant agent

may improve the understanding of the model by the participants''. Our system, exploiting

iObjects in the context of social virtual worlds, aims to work along those advantages too.

Another research conceives the organisation infrastructure of a multiagent system in terms

of agents and artifacts (Kitio et al.. 2007). They distinguish between organizational artifacts,

which provide organization’s functional aspects, and organizational agents, which provide

decision aspects of organizations management. Artifacts and iObjects, although both arise

with a similar objective, that is, to model “entities” used to develop activities in the

institutions, they are situated in different levels of abstraction. Artifacts facilitate agent

activities at a organizational MAS level and iObjects facilitate user interactions at 3D world

level.