The economic metaphor of Italian politics for dynamic coalition regeneration in the Robocup competition of Aibo robots

A. Chella, R. Sorbello, L. Martorana, M. Palermo, Rosamaria E. Barone
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Abstract

The variation version of the economic metaphor of Italian politics, an architecture that loosely takes inspiration from the political organizations of democratic governments, following the example of Italian government, and which provides a solution for the coordination of a spare colony of robots, is competent to allow the coordination of the behaviors of a team of four robots in order to play soccer in the Robocup competition. The development of an evolution of economic metaphor of Italian politics is now outlined. This new approach proposes a mechanism to make a new coalition caused by the failure of the government strategy and by a general inefficiency of the whole colony during the reaching of the mission targets, such as goals scored, faults committed and other soccer parameters (game evolution, score, time left, past team coalition performances). The main characteristic of the proposed frameworks lies in its dynamic reconfigurability in order to adapt the robot colony behaviors to high dynamic environmental changes choosing from time to time the best coalition capable to apply the most suitable soccer strategy, (from an extreme offensive to a total defensive), for the current game situation. To validate the effectiveness of our approach we have realized a framework based on the MissionLab robot simulation software developed at the Mobile Robot Lab of the Georgia Institute of Technology and we have transferred these framework inside the OPEN-R environment of the team of four Sony Aibo Ers-7 robots.
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在Aibo机器人世界杯比赛中,意大利政治对动态联盟再生的经济隐喻
意大利政治的经济隐喻的变体版本,一个松散地从民主政府的政治组织中获得灵感的建筑,以意大利政府为例,并为备用机器人殖民地的协调提供了解决方案,能够允许四个机器人团队的行为协调,以便在机器人世界杯比赛中踢足球。现在概述了意大利政治的经济隐喻演变的发展。这种新方法提出了一种机制,可以在政府策略失败和整个群体在达到任务目标(如进球、失误和其他足球参数(比赛演变、得分、剩余时间、过去的球队联盟表现)期间普遍效率低下的情况下建立新的联盟。所提出的框架的主要特点在于其动态可重构性,以便使机器人群体行为适应高动态环境变化,不时选择能够应用最合适的足球策略的最佳联盟,(从极端进攻到完全防守),为当前的比赛情况。为了验证我们方法的有效性,我们基于佐治亚理工学院移动机器人实验室开发的MissionLab机器人仿真软件实现了一个框架,我们已经将这些框架转移到四个索尼Aibo Ers-7机器人团队的OPEN-R环境中。
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