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Get Agents for Games and Simulations: Trends in Techniques, PDF

By Jakub Gemrot, Rudolf Kadlec, Michal Bída (auth.), Frank Dignum, Jeff Bradshaw, Barry Silverman, Willem van Doesburg (eds.)

ISBN-10: 3642111971

ISBN-13: 9783642111976

ISBN-10: 364211198X

ISBN-13: 9783642111983

Research on multi-agent structures has supplied a promising expertise for enforcing cognitive clever non-playing characters. even though, the applied sciences utilized in video game engines and multi-agent structures usually are not quite simply suitable as a result of a few inherent transformations in issues. the place online game engines concentrate on real-time features and therefore propagate potency and vital keep watch over, multi-agent systems think autonomy of the brokers. elevated autonomy and intelligence may well provide advantages for a extra compelling gameplay and will also be valuable for severe video games. even if, difficulties take place while present online game layout ideas are used to include state of the art multi-agent process know-how. a really comparable argument could be given for agent-based (social) simulation.

This quantity includes the papers offered at AGS 2009, the 1st foreign Workshop on brokers for video games and Simulations, held in Budapest on may well eleven, 2009. the focal point of the workshop was once at the specific demanding situations dealing with these utilizing agent expertise for video games and simulations, with issues overlaying the technical, conceptual and layout elements of the field.

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G. a freshly launched JVMs, no allocated memory etc. 4 Overall System Load The objective of the first experiment was to explore how the speed of the simulation changes with the changing level of system load. The experiment was performed using all computer nodes. The variations in system load were introduced by varying the number of airplanes simulated, ranging from 10% up to 100% of all air-traffic (with 10% step). 4GHz) 4 GB RAM Windows Vista 64-bit 3 cores 4GB used for Flight control 5 cores 4GB used for Environment simulation Fig.

33–47, 2009. c Springer-Verlag Berlin Heidelberg 2009 34 M. K¨ oster et al. for reactive systems. It draws a strict distinction between the knowledge representation (KR) and behavioural aspects of an agent program and thus enables exploiting heterogeneous KR technologies in a single agent system. To provide a proof-of-concept, as well as to further nurture our research towards a methodology of development with Jazzyk BSM (cf. [14] and [13]), we developed two case study applications Jazzbot and Urbibot .

This number is used to normalize run-time to study requirements per each situated entity. 3 Testing Configuration The configuration contained a set of several heterogenous (both in terms of the operating system and hardware) computer nodes. During experiments, nodes were dedicated for ESCs or deliberative controllers, see computer node allocation in Figure 4: The testing configuration consisted of 9 cores with 9GB RAM for ESCs and 11 cores with 15GB RAM for the flight control integrated in deliberative controllers.

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Agents for Games and Simulations: Trends in Techniques, Concepts and Design by Jakub Gemrot, Rudolf Kadlec, Michal Bída (auth.), Frank Dignum, Jeff Bradshaw, Barry Silverman, Willem van Doesburg (eds.)


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