Decoupling Cognitive Agents and Virtual Environments

The development of and accessibility to rich virtual environments, both for recreation and training activities leads to the use of intelligent agents to control avatars (and other entities) in these environments. There is a fundamental tension in such systems between tight integration, for performance and low coupling, for generality, flexibility and extensibility. This paper addresses the engineering issues in connecting agent platforms and other software entities with virtual environments, driven by the following informal requirements: (i) accessibility: we would like (easily) to be able to connect any (legacy) software component with the virtual environment (ii) performance: we want the benefits of decoupling, but not at a high price in performance (iii) distribution: we would like to be able to locate functionality where needed, when necessary, but also be location agnostic otherwise (iv) scalability: we would like to support large-scale and geographically dispersed virtual environments. We start from the position that the basic currency unit of such systems can be events. We describe the Bath Sensor Framework, which is a middleware that attempts to satisfy the above goals and to provide a low-latency linking mechanism between event producers and event consumers, while minimising the effect of coupling of components. We illustrate the framework in two complementary case studies using the Jason agent platform, Second Life and AGAVE (a 3D VE for vehicles). Through these examples, we are able to carry out a preliminary evaluation of the approach against the factors above, against alternative systems and demonstrate effective distributed execution.

[1]  Jörg P. Müller,et al.  The Design of Intelligent Agents , 1996, Lecture Notes in Computer Science.

[2]  Charles M. Macal,et al.  Action Selection and Individuation in Agent Based Modelling , 2003 .

[3]  Marc Esteva,et al.  Teaching Autonomous Agents to Move in a Believable Manner within Virtual Institutions , 2008, IFIP AI.

[4]  R. A. Brooks,et al.  Intelligence without Representation , 1991, Artif. Intell..

[5]  V. D. Veksler Second Life as a Simulation Environment : Rich , high-fidelity world , minus the hassles , 2009 .

[6]  Sebastien Goasguen,et al.  Kestrel: an XMPP-based framework for many task computing applications , 2009, MTAGS '09.

[7]  Egon L. Willighagen,et al.  XMPP for cloud computing in bioinformatics supporting discovery and invocation of asynchronous web services , 2009, BMC Bioinformatics.

[8]  Marc Esteva,et al.  Virtual Institutions: Normative Environments Facilitating Imitation Learning in Virtual Agents , 2008, IVA.

[9]  Martin K. Purvis,et al.  Interfacing a cognitive agent platform with a virtual world: a case study using Second Life , 2011, AAMAS.

[10]  Alessandro Ricci,et al.  Environment programming in multi-agent systems: an artifact-based perspective , 2011, Autonomous Agents and Multi-Agent Systems.

[11]  C. Bergenhem CHALLENGES OF PLATOONING ON PUBLIC MOTORWAYS , 2010 .

[12]  Lin Padgham,et al.  Agent-Oriented Software Engineering VIII, 8th International Workshop, AOSE 2007, Honolulu, HI, USA, May 14, 2007, Revised Selected Papers , 2008, AOSE.

[13]  David Bernstein,et al.  Intercloud Directory and Exchange Protocol Detail Using XMPP and RDF , 2010, 2010 6th World Congress on Services.

[14]  Frank Dignum Agents for games and simulations , 2011, Autonomous Agents and Multi-Agent Systems.

[15]  John R. Anderson,et al.  ACT-R: A Theory of Higher Level Cognition and Its Relation to Visual Attention , 1997, Hum. Comput. Interact..

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

[17]  Marc Esteva,et al.  A Methodology for Developing Multiagent Systems as 3D Electronic Institutions , 2007, AOSE.

[18]  Mario Gerla,et al.  INTER-VEHICULAR COMMUNICATIONS , 2006, IEEE Wireless Communications.

[19]  Frank Dignum,et al.  CIGA: A Middleware for Intelligent Agents in Virtual Environments , 2011, AEGS.

[20]  K. VanLehn Architectures for Intelligence , 1999 .

[21]  C. Brom Action selection for Intelligent Systems , 2006 .

[22]  Jörg P. Müller,et al.  The agent architecture interrap , 1996 .

[23]  Pradeep Dubey,et al.  Second Life and the New Generation of Virtual Worlds , 2008, Computer.

[24]  Richard Fikes,et al.  Learning and Executing Generalized Robot Plans , 1993, Artif. Intell..

[25]  Marina De Vos,et al.  On-line reasoning for institutionally-situated BDI agents , 2011, AAMAS.

[26]  Ahmed Benmimoun,et al.  Challenges of Platooning on Public Motorways , 2010 .

[27]  Michael Wooldridge,et al.  Programming Multi-Agent Systems in AgentSpeak using Jason (Wiley Series in Agent Technology) , 2007 .

[28]  Jörg Ott,et al.  10402 Abstracts Collection and Executive Summary - Inter-Vehicular Communication , 2010, Inter-Vehicular Communication.

[29]  Peter Van Roy,et al.  Self Management and the Future of Software Design , 2007, FACS.

[30]  Rodney A. Brooks,et al.  How to Build Complete Creatures Rather than Isolated Cognitive Simulators , 2014 .

[31]  Mark Rejhon,et al.  In-Band Real Time Text , 2013 .

[32]  Marina De Vos,et al.  Normative Run-Time Reasoning for Institutionally-Situated BDI Agents , 2011, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology.

[33]  Deepak Vij 1 Using XMPP as a transport in Intercloud Protocols , 2010 .

[34]  Innes A. Ferguson,et al.  Touring Machines: autonomous agents with attitudes , 1992, Computer.

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

[36]  Andrew N. Marshall,et al.  Gamebots: A 3D Virtual World Test-Bed For Multi-Agent Research , 2001 .

[37]  Davide Ancona,et al.  Languages for Programming BDI-style Agents: an Overview , 2005, WOA.

[38]  Max Bramer,et al.  Artificial Intelligence in Theory and Practice II , 2009 .

[39]  Martin K. Purvis,et al.  IDENTIFYING EVENTS TAKING PLACE IN SECOND LIFE VIRTUAL ENVIRONMENTS , 2012, Appl. Artif. Intell..