Biologically-Inspired Collaborative Computing: IFIP 20th by Marco Dorigo (auth.), Mike Hinchey, Anastasia Pagnoni, Franz

By Marco Dorigo (auth.), Mike Hinchey, Anastasia Pagnoni, Franz J. Rammig, Hartmut Schmeck (eds.)

International Federation for info Processing

The IFIP sequence publishes cutting-edge ends up in the sciences and applied sciences of knowledge and communique. The scope of the sequence comprises: foundations of machine technological know-how; software program thought and perform; schooling; laptop purposes in expertise; communique platforms; platforms modeling and optimization; info structures; pcs and society; computers expertise; protection and defense in info processing structures; man made intelligence; and human-computer interplay. complaints and post-proceedings of refereed foreign meetings in desktop technology and interdisciplinary fields are featured. those effects usually precede magazine booklet and symbolize the most up-tp-date examine. The valuable target of the IFIP sequence is to motivate schooling and the dissemination and alternate of knowledge approximately all elements of computing.

For additional info concerning the three hundred different books within the IFIP sequence, please stopover at

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Extra resources for Biologically-Inspired Collaborative Computing: IFIP 20th World Computer Congress, Second IFIP TC 10 International Conference on Biologically-Inspired Collaborative Computing, September 8–9, 2008, Milano, Italy

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For small number of agents (less than 110) the system without congestion control is the second most fair system. For larger number of agents the system with method CP is the second best. 6 Conclusions In this paper we have studied the problem of congestion control agent systems with ant inspired movement rules. In the studied systems the agents have to visit a service station to refill their energy storage. Three methods for self-organized congestion control have been proposed. It was shown experimentally that the proposed methods can significantly reduce the congestion and are also fair for systems with a larger number of agents.

A forward ant contains the search algorithm that is executed by the ant on arriving at a node. The search algorithm performs a linear search for the terms in the user’s search query encapsulated by the ant over the resources present on a node and returns a success only if there is a match. 3. Model Our model of the p2p network comprises a connected network of N nodes. Each node contains certain resources inside a resource table and a resource can be identified on a node with a unique identifier.

Each wall has an small opening in the middle that is next to the service station. The idea of this method is that slow agents with small value of µi might be forced to wait behind a wall and therefore do not block the service station. Hence, the agents that have visited the service station can move away from it. An example for this control method CW can be seen in the middle of Figure 3. The third control method CD is to change the behavior of the agents slightly. Here the sensing range σi of agent i depends on the internal parameter µi .

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