By Aizhong Lin, Igor Hawryszkiewycz, Brian Henderson-Sellers (auth.), Paolo Bresciani, Paolo Giorgini, Brian Henderson-Sellers, Graham Low, Michael Winikoff (eds.)
Information structures became the spine of every kind of agencies - day. In nearly each region – production, schooling, overall healthiness care, govt and companies huge and small – details structures are relied upon for - eryday paintings, verbal exchange, info collecting and decision-making. but, the in?exibilities in present applied sciences and techniques have additionally ended in bad functionality, incompatibilities and hindrances to alter. As many firms are reinventing themselves to fulfill the demanding situations of worldwide festival and e-commerce, there's expanding strain to boost and installation new applied sciences which are ?exible, strong and attentive to quick and unforeseen switch. Agent suggestions carry nice promise for responding to the recent realities of - formation platforms. They o?er higher-level abstractions and mechanisms which deal with matters similar to wisdom illustration and reasoning, communique, coordination, cooperation between heterogeneous and self reliant events, p- ception, commitments, pursuits, ideals, intentions, etc., all of which want conc- tual modelling. at the one hand, the concrete implementation of those thoughts can result in complicated functionalities, e.g., in inference-based question answering, transaction regulate, adaptive paintings ?ows, brokering and integration of disparate info assets, and automatic conversation procedures. nevertheless, their wealthy representational functions permit for extra trustworthy and ?- ible remedies of advanced organizational methods, resulting in extra e?ective standards research and architectural/detailed design.
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Additional info for Agent-Oriented Information Systems II: 6th International Bi-Conference Workshop, AOIS 2004, Riga, Latvia, June 8, 2004, and New York, NY, USA, July 20, 2004, Revised Selected Papers
An overview of each agent is given below. UIA: The UIA provides an interface for the user. In addition, it detects the user’s situation and copes with his/her various situations. Upon receiving the user’s request, it considers the situation at the moment and outputs a script that carries out the user’s processing. For the purpose of achieving these functions, the UIA contains a logic language processing system (hereafter referred to as “inference engine”). In order to cope with various situations, the system designer describes behaviour of the agent corresponding to such situations by using logic language rules (hereafter referred to as “reasoning rules”).
It also copes with switching the terminal that the user is using. In order to do this, a script contains instructions for autonomously migrating between hosts. Potential causes of terminal instability include power loss and network disconnection due to changes in the location of users. For example, in the case of a web information search, the user may turn oﬀ the portable terminal or the network may be disconnected because the terminal has changed its location. In order to cope with such instability, the PA transfers the necessary information to the agent pool after receiving it from the UIA.
Further information about all the extended set of GPGP coordination mechanisms and the actual application of these mechanisms can be found in [2, 3, 17]. 3 EMS Model We do not intend to simulate the exact real world EMS. The objective of this paper is to demonstrate the effectiveness of our extended set of GPGP coordination mechanisms in this selected information system, EMS. This EMS model is similar to the real EMS systems under certain assumptions and selected environmental settings. In order to suit our model to larger-scale disasters with more participating agencies, we add a police department into the traditional EMS model.