By Longbing Cao
This e-book constitutes the completely refereed and revised chosen papers from the tenth foreign Workshop on brokers and information Mining Interactions, ADMI 2014, held in Paris, France, in could 2014 as satellite tv for pc workshop of AAMAS 2014, the thirteenth foreign convention on self sustaining brokers and Multiagent Systems.
The eleven papers provided have been conscientiously reviewed and chosen from a variety of submissions for inclusion during this quantity. They current present examine and engineering effects, in addition to strength demanding situations and clients encountered within the respective groups and the coupling among brokers and information mining.
Read or Download Agents and Data Mining Interaction: 10th International Workshop, ADMI 2014, Paris, France, May 5-9, 2014, Revised Selected Papers PDF
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Additional info for Agents and Data Mining Interaction: 10th International Workshop, ADMI 2014, Paris, France, May 5-9, 2014, Revised Selected Papers
36 Z. Li et al. The two aspects of temporal dynamics in multiplex networks can both inevitably postpone time to reach stationary state since the activation of conjoint agent is delayed and information spreads on the topologically ineﬃcient path. Moreover, the estimation of inﬂuential layer in multiplex networks can be varied by temporal dynamics apart from structural diﬀerences and propagation conditions between multiple layers. In real life, the social network is inﬂuential if it contains numerous active users and provides convenient channels of sharing information.
The numerical modeling also exhibits the feature that temporal dynamics do not aﬀect the ﬁnal scale of active agents if enough time of propagation is given. Due to the topological diﬀerences between G1 and G2 , the ﬁnal size of propagation in Fig. 4(h) is much larger than the one in Figure (i). 2 Eﬀects of Two Aspects of Temporal Dynamics The main object of this section is to show the eﬀects of two aspects of temporal dynamics on information propagation in multiplex networks as analyzed in the two case studies.
3(a) and more agents in G1 are activated by conjoint agents in Fig. 3(b). Combining cross-layers delay with intra-layer delay, more information about propagation process in multiplex networks can be found. 4 Simulation The temporal propagation dynamics in multiplex networks has been simulated on a computer. Multiplex networks are synthetic and contain two layers since real datasets of multiplex networks are still rare. G1 is the Enron email network with os-R´enyi network with 36692 agents and average 10 neighbors and G2 is Erd¨ identical number of agents and average degree.
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