Download Agents for Educational Games and Simulations: International by Surangika Ranathunga, Stephen Cranefield (auth.), Martin PDF

By Surangika Ranathunga, Stephen Cranefield (auth.), Martin Beer, Cyril Brom, Frank Dignum, Von-Wun Soo (eds.)

ISBN-10: 3642323251

ISBN-13: 9783642323256

This publication is composed more often than not of revised papers that have been provided on the brokers for tutorial video games and Simulation (AEGS) workshop hung on may perhaps 2, 2011, as a part of the self sufficient brokers and MultiAgent platforms (AAMAS) convention in Taipei, Taiwan. The 12 complete papers provided have been conscientiously reviewed and chosen from a number of submissions. The papers are equipped topical sections on middleware purposes, dialogues and studying, adaption and convergence, and agent applications.

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Additional info for Agents for Educational Games and Simulations: International Workshop, AEGS 2011, Taipei, Taiwan, May 2, 2011. Revised Papers

Sample text

It is often used in research on embodied agents mainly because of the lack of good alternatives for accessing virtual environments [7,9]. Gamebots can be compared to CIGA’s GE Interface layer (see Figure 3). Though, in Gamebots, there is no methodology for using domain ontologies as the interface messages are fixed and geared specifically towards the UT engine. Further, action monitoring is not supported since Gamebots doesn’t offer explicit execution and monitoring of actions. The High Level Architecture (HLA) is an architecture for distributed simulations.

Olivier, P. ) IVA 2006. LNCS (LNAI), vol. 4133, pp. 205–217. Springer, Heidelberg (2006) 13. : Agents, games and hla. Simulation Modelling Practice and Theory 14(6), 752–767 (2006) 14. : Applying ”design by contract”. Computer 25, 40–51 (1992) 15. : Smart objects for attentive agents. In: WSCG (2003) 16. : Towards Integrating AI Story Controllers and Game Engines: Reconciling World State Representations. In: Proceedings of the 2005 IJCAI Workshop on Reasoning, Representation and Learning in Computer Games (2005) 17.

1 Introduction Reactive planning is currently the dominant paradigm for controlling virtual agents in 3D videogames and simulations. Prominent reactive planning techniques used in the industry are derivations of finite state machines (FSMs) [1], and more recently, behavior trees [2]. Technically, these are implemented in a scripting language, be it a M. Beer et al. ): AEGS 2011, LNAI 7471, pp. 38–62, 2012. © Springer-Verlag Berlin Heidelberg 2012 An Experimental Pilot Study with Human Subjects 39 general-purpose language such as Lua [3] or a special-purpose language tailored at a particular game, such as UnrealScript [4], or hard-coded in a game’s native language, typically C++ [5].

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Agents for Educational Games and Simulations: International Workshop, AEGS 2011, Taipei, Taiwan, May 2, 2011. Revised Papers by Surangika Ranathunga, Stephen Cranefield (auth.), Martin Beer, Cyril Brom, Frank Dignum, Von-Wun Soo (eds.)


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