Authors:
Ramoni O. Lasisi
and
Vicki H. Allan
Affiliation:
Utah State University, United States
Keyword(s):
Agents, Weighted voting games, Power indices, False-name manipulation, Annexation, Merging.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Cooperation and Coordination
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Group Decision Making
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Multi-Agent Systems
;
Software Engineering
;
Symbolic Systems
Abstract:
Weighted voting games are classic cooperative games which provide a compact representation for coalition
formation models in multiagent systems. We consider manipulation in weighted voting games via annexation
and merging, which involves an agent or some agents misrepresenting their identities in anticipation of gaining
more power at the expense of other agents in a game.We show that annexation and merging in weighted voting
games can be more serious than as presented in the previous work. Specifically, using similar assumptions as
employed in a previous work, we show that manipulators need to do only a polynomial amount of work
to find a much improved power gain, and then present two search-based pseudo-polynomial algorithms that
manipulators can use. We empirically evaluate our search-based method for annexation and merging. Our
method is shown to achieve significant improvement in benefits for manipulating agents in several numerical
experiments. While our search-based method achi
eves improvement in benefits of over 300% more than those
of the previous work in annexation, the improvement in benefits is 28% to 45% more than those of the previous
work in merging for all the weighted voting games we considered.
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