MAS Controlled NPCs in 3D Virtual Learning Environment

Incorporating intelligence and social behaviours into virtual worlds for learning is becoming more desirable in making them smart, adaptive, personalized, and therefore, more effective and engaging. Realistic non-player controlled characters (NPCs) are essential of a game world and are making the virtual world more real for players. This is true in video games where more interactive NPCs support the story narrative of a game, making the game more immersive, more convincing, but it is also true in other areas where virtual worlds are used such as business and education, increasing the effectiveness of those environments. Research that has been done with virtual agents and multi-agent systems can be leveraged to create more realistic NPCs through purposeful communication channels, inter-agent interactions and environment-agent interactions for game-based learning applications. This research proposes an approach to controlling avatars with intelligent agents through the creation of an interface between a multi-agent system to a virtual world engine. Basic NPC behaviours controlled by agents using Jason Agent Speak are used to test the feasibility of the approach. A Quizmaster is designed and illustrated as a proof of concept of the use of such agent controlled avatars in educational context.

[1]  Anand S. Rao,et al.  BDI Agents: From Theory to Practice , 1995, ICMAS.

[2]  Fuhua Lin,et al.  QuizMASter - A Multi-Agent Game-Style Learning Activity , 2009, Edutainment.

[3]  Paul Benjamin,et al.  A framework for building intelligent software assistants for virtual worlds , 2011 .

[4]  Jonathan Dinerstein,et al.  Fast multi-level adaptation for interactive autonomous characters , 2005, TOGS.

[5]  Chang-Hyun Jo,et al.  A new approach to the BDI agent-based modeling , 2004, SAC '04.

[6]  Barry G. Silverman,et al.  NonKin Village: An Embeddable Training Game Generator for Learning Cultural Terrain and Sustainable Counter-Insurgent Operations , 2009, AGS.

[7]  Rudolf Kadlec,et al.  Pogamut 3 Can Assist Developers in Building AI (Not Only) for Their Videogame Agents , 2009, AGS.

[8]  Mat Buckland,et al.  Programming Game AI by Example , 2004 .

[9]  Michael J. Jacobson,et al.  Designs for learning environments of the future : international perspectives from the learning sciences , 2010 .

[10]  Chunyan Miao,et al.  Design Perspectives for Learning in Virtual Worlds , 2010 .

[11]  Nicole Yankelovich,et al.  Open Wonderland: An Extensible Virtual World Architecture , 2011, IEEE Internet Computing.

[12]  Manuela M. Veloso,et al.  GameBots: a flexible test bed for multiagent team research , 2002, CACM.

[13]  Ana Paiva,et al.  Creating adaptive affective autonomous NPCs , 2012, Autonomous Agents and Multi-Agent Systems.

[14]  Fuhua Lin,et al.  An Approach for Integrating 3D Virtual Worlds with Multiagent Systems , 2011, 2011 IEEE Workshops of International Conference on Advanced Information Networking and Applications.

[15]  Timothy K. Shih,et al.  A Conceptual Design of Multi-Agent Based Personalized Quiz Game , 2011, 2011 IEEE 11th International Conference on Advanced Learning Technologies.

[16]  Steve Leung,et al.  TSI-Enhanced Pedagogical Agents to Engage Learners in Virtual Worlds , 2013, Int. J. Distance Educ. Technol..