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.)

This publication is composed commonly of revised papers that have been provided on the brokers for academic video games and Simulation (AEGS) workshop hung on may possibly 2, 2011, as a part of the self reliant brokers and MultiAgent platforms (AAMAS) convention in Taipei, Taiwan. The 12 complete papers offered have been rigorously reviewed and chosen from a variety of submissions. The papers are geared up topical sections on middleware purposes, dialogues and studying, adaption and convergence, and agent applications.

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

Sample text

Creating semantic data from raw data at runtime is a process performed in the GE Interface layer. g. associating the fire concept to a fire class in the game engine). g. an object’s size property is calculated). This translation process is performed when agents sense environment entities. Furthermore, semantic event classes can be generated based on raw game events or as a result of custom inferences. Inference based on previously sensed information is achieved using a cache belonging to an agent’s sensory processor.

For both the tasks and in both programming environments, the students’ task was to organize low-level action and sensory primitives to produce complex behavior, but not to program the primitives as such. The drag-and-drop graphical editor we developed for POSH disguised its Lisp-like underlying plan syntax students might have struggled with. The study was only possible because the Pogamut platform provided the same development environment for both tasks and allowed us to predesign the same sets of behavior primitives, isolating the features of the language as the subject of the study.

Agents for Games and Simulations II. LNCS, vol. 6525, pp. 19–37. Springer, Heidelberg (2011) 10. : Pogamut 3 Can Assist Developers in Building AI (Not Only) for Their Videogame Agents. , van Doesburg, W. ) Agents for Games and Simulations. LNCS, vol. 5920, pp. 1–15. Springer, Heidelberg (2009) 11. : Modeling objects for interaction tasks. In: Proc. Eurographics Workshop on Animation and Simulation, pp. 73–86 (1998) 12. : Towards a Common Framework for Multimodal Generation: The Behavior Markup Language.

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