By Andrew W. Wicker, Jon Doyle (auth.), Francien Dechesne, Hiromitsu Hattori, Adriaan ter Mors, Jose Miguel Such, Danny Weyns, Frank Dignum (eds.)
This publication constitutes the completely refereed post-workshop court cases of five workshops, held on the tenth overseas convention on self sufficient brokers and Multiagent platforms, AAMAS 2011, in Taipei, Taiwan, could 2-6, 2011. The 37 revised complete papers offered including 1 invited paper have been rigorously reviewed and chosen from a number of submissions. The papers are equipped in sections at the workshops Agent-Based Modeling for coverage Engineering (AMPLE), Agent-Oriented software program Engineering (AOSE), self reliant Robots and Multirobot platforms (ARMS), facts orientated positive Mining and Multi-Agent Simulation, vastly Multi-Agent structures: types, equipment and instruments (DOCM³AS), and Infrastructures and instruments for Multiagent structures (ITMAS).
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Additional info for Advanced Agent Technology: AAMAS 2011 Workshops, AMPLE, AOSE, ARMS, DOCM3AS, ITMAS, Taipei, Taiwan, May 2-6, 2011. Revised Selected Papers
Micro- and macro-level validation in agentbased simulation. J. Artiﬁcial Societies and Social Simulation 11(2:9) (2008) 54. : Understanding MABS and social simulation: Switching between languages in a hierarchy of levels. J. Artiﬁcial Societies and Social Simulation 7(4:5) (2004) 55. The World Bank: Helping countries combat corruption: The role of the World Bank, poverty reduction and economic management network. Tech. rep (1997) 56. Transparency International: The global corruption report 2009.
Once a water bank is enabled, policy-makers may regulate how trading is made and by so doing, have a direct inﬂuence on demand and with that foster a “good” use of water. In this paper, we present a decision-support environment constructed around a water-rights market. It is designed so that policy-makers may explore the interplay between i) market regulations, ii) trader proﬁles and market composition, and iii) the aggregated outcomes of trading under those set conditions. Our environment is designed as a multi-agent system that implements market regulations and is enabled with tools to specify performance indicators, to spawn agent populations and allow humans as well as software agents to participate in simulations of virtual trading.
Figure 2 presents the model’s graphical structure. We defined three entities (Population, Nature and Police) and 18 quantities, where 6 are similar to the Base model and 12 are additional ones. Moreover, based on the research conclusions we defined influence (I) among different variables. For example, emotional event increases the existence of violent core among the participants. BIU Model. The third model, BIU model, is our own novel extension of the Police model. Based on interviews with social and cognitive scientists, as well as additional literature surveys, we added four additional variables, and updated 19 influences (relations) among the variables.