Sarjoughian, H., B.P. Zeigler, and S.B. Hall, A Layered Modeling and Simulation Architecture for Agent-based System Development. IEEE Proceedings, 2001. 89(2): p. 201-13.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....domains likewise. Providing different component libraries for different domains is one step towards the solution. A support of continuous as well as discrete simulation and an easy extensibility at the simulation and experimental level ask for a layered and component based approach, e.g. [27, 31]. Testing in the large implies to simulate the real environment the agent is supposed to work in. Like scenarios that are used for a testing in the small, scenarios for a testing in the large vary with the type of agents envisioned. Thus, problems and accordingly probable solutions appear to be ....

....only be analyzed based on their observable behavior within the virtual environment. One would like to have both. On the one hand the possibility should be given to execute agents as they are and to switch arbitrarily between an execution in the real environment and the virtual test environment [35, 31]. On the other hand, agents should be an integral part of the experimental setting and as such perceivable and controllable. In analyzing the behavior of agents, models focus the view on relevant aspects and changes within agents. Thus, tools should support a graceful transformation from ....

H. Sarjoughian, B.P. Zeigler, and S.B. Hall. A Layered Modeling and Simulation Architecture for Agent-Based System Development. Proceedings of the IEEE, 89(2):201--213, 2001.

....preliminary investigations of an algorithm for dynamic multicast grouping for HLA. Saville et al. Saville 1997) describe GRIDS, a generic runtime infrastructure which utilises dynamic instantiation of Java classes in order to achieve Interest Management. The Joint MEASURE system (Hall, Zeigler Sarjoughian 1999, Hall 2000, Sarjoughian, Zeigler Hall 2000) is implemented on top of HLA and utilises event distribution and predictive encounter controllers to efficiently manage interactions among entities. However, despite these efforts, the problem of dynamic interest management remains largely unsolved. 3 Load ....

....an algorithm for dynamic multicast grouping for HLA. Saville et al. Saville 1997) describe GRIDS, a generic runtime infrastructure which utilises dynamic instantiation of Java classes in order to achieve Interest Management. The Joint MEASURE system (Hall, Zeigler Sarjoughian 1999, Hall 2000, Sarjoughian, Zeigler Hall 2000) is implemented on top of HLA and utilises event distribution and predictive encounter controllers to efficiently manage interactions among entities. However, despite these efforts, the problem of dynamic interest management remains largely unsolved. 3 Load Balancing The synchronisation ....

Sarjoughian, H. S., Zeigler, B. P. & Hall, S. B. (2000), `A layered modeling and simulation architecture for agentbased system development', Proceedings of the IEEE.

....James [56] This approach renders an additional modeling of agents super uous, as they can be tested as they are. This plug and test has also been raised as a requirement in testing multi agent systems, e.g. in the contributions by Logan and Theodoropoulos [36] and Sarjoughian and his colleagues [49]. In James, the entire Mole agents with their states can be plugged into the virtual world. Therefore, a conservative variant of the above optimistic strategy has been developed, which allows simulation and deliberation to proceed concurrently however which avoids rollbacks from the outset. ....

H. Sarjoughian, B.P. Zeigler, and S.B. Hall. A Layered Modeling and Simulation Architecture for Agent-Based System Development. Proceedings of the IEEE, 89(2):201-213, 2001.

....on preliminary investigations on a dynamic algorithm for dynamic multicast grouping for HLA. Saville et al. 27] describe GRIDS, a generic runtime infrastructure which utilises dynamic instantiation of Java classes in order to achieve Interest Management. The Joint MEASURE system [28] 29] [30] is implemented on top of HLA and utilises event distribution and predictive encounter controllers to efficiently manage interactions among entities. However, despite these efforts, the problem of dynamic interest management remains largely unsolved. In the remainder of this paper we present a new ....

....example, Gensim [42] and SIM AGENT [41] but means that every state variable must be accessed in order to determine which objects in the environment (agents, obstacles or food items) are visible to an agent. Unless the state variables are grouped in some way based on their values (see, e.g. 5] [30]) this means that all state variables lie within the sphere of influence of each vision event and hence of each agent. TABLE II PROBABILITY THAT A RANDOMLY SELECTED STATE VARIABLE ACCESSED BY ONE PREY AGENT WILL BE ACCESSED BY EXACTLY n PREY AGENTS. Prey 1 2 3 4 5 5 0.584 0.211 0.050 0.002 ....

Hessam S. Sarjoughian, Bernard P. Zeigler, and Steven B. Hall, "A layered modeling and simulation architecture for agent-based system development, " Proceedings of the IEEE, 2000.

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Sarjoughian, H., B.P. Zeigler, and S.B. Hall, A Layered Modeling and Simulation Architecture for Agent-based System Development. IEEE Proceedings, 2001. 89(2): p. 201-13.

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