3,057 research outputs found
The Emergence of Norms via Contextual Agreements in Open Societies
This paper explores the emergence of norms in agents' societies when agents
play multiple -even incompatible- roles in their social contexts
simultaneously, and have limited interaction ranges. Specifically, this article
proposes two reinforcement learning methods for agents to compute agreements on
strategies for using common resources to perform joint tasks. The computation
of norms by considering agents' playing multiple roles in their social contexts
has not been studied before. To make the problem even more realistic for open
societies, we do not assume that agents share knowledge on their common
resources. So, they have to compute semantic agreements towards performing
their joint actions. %The paper reports on an empirical study of whether and
how efficiently societies of agents converge to norms, exploring the proposed
social learning processes w.r.t. different society sizes, and the ways agents
are connected. The results reported are very encouraging, regarding the speed
of the learning process as well as the convergence rate, even in quite complex
settings
Computer Science and Game Theory: A Brief Survey
There has been a remarkable increase in work at the interface of computer
science and game theory in the past decade. In this article I survey some of
the main themes of work in the area, with a focus on the work in computer
science. Given the length constraints, I make no attempt at being
comprehensive, especially since other surveys are also available, and a
comprehensive survey book will appear shortly.Comment: To appear; Palgrave Dictionary of Economic
Evolution of Cooperation among Mobile Agents
We study the effects of mobility on the evolution of cooperation among mobile
players, which imitate collective motion of biological flocks and interact with
neighbors within a prescribed radius . Adopting the prisoner's dilemma game
and the snowdrift game as metaphors, we find that cooperation can be maintained
and even enhanced for low velocities and small payoff parameters, when compared
with the case that all agents do not move. But such enhancement of cooperation
is largely determined by the value of , and for modest values of , there
is an optimal value of velocity to induce the maximum cooperation level.
Besides, we find that intermediate values of or initial population
densities are most favorable for cooperation, when the velocity is fixed.
Depending on the payoff parameters, the system can reach an absorbing state of
cooperation when the snowdrift game is played. Our findings may help
understanding the relations between individual mobility and cooperative
behavior in social systems.Comment: 15 pages, 5 figure
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