Titlebook: Bio-Inspired Models of Network, Information, and Computing Systems; 5th International IC Junichi Suzuki,Tadashi Nakano Conference proceedin

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P2P-Based Scalable Execution Platform for Algorithmically Transitive Networkard propagation propelled with node firing and token creation, a backward propagation caused by evaluating differential coefficients, and a topological alteration taken place by autonomous agents. In the research of the ATN, a simulation run on some parallel processing scheme is essential. As a flex

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Biologically Inspired Modeling of Smart Grid for Dynamic Power-Flow Controlated the basic equations for the smart grid by inspiring from the mechanisms in biological organism, and controled the power-flow dynamically in the smart grid by monitoring an objective function, which reflects the power-flow and the constraint imposing on the power nodes. To validate the operation

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Path Heuristics Using ACO for Inter-domain Routing in Mobile Ad Hoc and Sensor Networkssical topology control techniques for routing in sensor networks, the use of geographical coordinates has been investigated for self-organized and fully distributed message forwarding. However, the identification of the nodes’ positions is either expensive in terms of necessary equipment or message

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Coevolution of Game Strategies, Game Structures and Network Structuresproach, we constructed a coevolutionary model of game strategies and network modification strategies, in which individuals can evolve the game structure by developing new strategies that expand the existing payoff properties of Prisoner’s Dilemma (PD) and Symmetric Coordination (SC). Evolutionary ex

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Reconstructing History of Social Network Evolution Using Web Search Enginesare rather difficult to obtain experimentally in conventional research methods. In the proposed method, a search query string is combined with additional keywords that specify inclusion/exclusion of specific years to limit the search results to a particular time point. Using the proposed method, we

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Learning and Generalization in Random Automata Networksing examples is provided for learning. Here, we extend this body of work and show experimentally that random Boolean networks (RBNs), where both the interconnections and the Boolean transfer functions are chosen at random initially, can be evolved by using a state-topology evolution to solve simple

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