By Hoa Khanh Dam, Jeremy Pitt, Yang Xu, Guido Governatori, Takayuki Ito
This booklet constitutes the refereed complaints of the seventeenth foreign convention on rules and perform of Multi-Agent structures, PRIMA 2014, held in Gold Coast, QLD, Australia, in December 2014.
The convention was once co-located with the thirteenth Pacific RIM overseas convention on man made Intelligence, PRICAI 2014.
The 21 revised complete papers awarded including 15 brief papers have been rigorously reviewed and chosen from seventy seven submissions. The papers are prepared in topical sections on self association and social networks/crowdsourcing; common sense and argumentation; simulation and insurance; interplay and functions; norms, video games and social selection; and metrics, optimisation, negotiation and learning.
Read or Download PRIMA 2014: Principles and Practice of Multi-Agent Systems: 17th International Conference, Gold Coast, QLD Australia, December 1-5, 2014. Proceedings PDF
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Additional info for PRIMA 2014: Principles and Practice of Multi-Agent Systems: 17th International Conference, Gold Coast, QLD Australia, December 1-5, 2014. Proceedings
Example text
J. ) AOSE 2009. LNCS, vol. 6038, pp. 191–212. Springer, Heidelberg (2011) 31. org/wikis/openup/ (accessed September 2, 2013) 32. : Openup – the best of two worlds. Methods & Tools (2008) Experiments with Social Capital in Multi-agent Systems Patricio E. uk Abstract. Social scientist define social capital as a feature or attribute of an organisation or an individual that facilitates cooperation to achieve mutual benefit and enhances their ability to solve collective action problems. In this paper we present a set of experiments on an electronic version of social capital in two different scenarios of repeated pairwise interactions amongst agents.
Algorithm 1 shows a step-by-step procedure of the cooperation game. At the beginning of each round, random pairs of agents are generated and a specific pairwise game is selected for each of the pairs. We called this a Match. Then, players select the action they want to play in that scenario (lines 9-11). At the end of the round the players actions are grouped with their matches and the outcome is calculated (line 13). Here players will gain or lose points based on their actions and the game’s payoff matrix (line 14).
Decentralized Approaches for Self-Adaptation in Agent Organizations. ACM Transactions on Autonomous and Adaptive Systems 7(1), 1 (2012) Estimating the Degrees of Neighboring Nodes in Online Social Networks Jooyoung Lee1 and Jae C. edu Abstract. , node) in a social network can use to estimate each of its neighbor’s degree. The knowledge about the degrees of neighboring nodes is useful for many existing algorithms in social networks studies. For example, algorithms to estimate the diffusion rate of information spread need such information.