Advanced cooperative decentralized decision making using a cooperative reward system

P. Pascheka, Michael During
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引用次数: 7

Abstract

Agents can benefit from cooperative behavior as it intends to increase the total utility. In traffic situations, one agent may behave cooperatively by yielding to another. In recurring situations, this may lead to an imbalanced distribution of the benefit. However, humans prefer balanced utility distributions over imbalanced ones. While state-of-the-art cooperative decentralized decision making may promote such an imbalanced utility distribution, advanced cooperative decentralized decision making can support equality among the agents. Three different approaches are compared: Considering the agents' utilities perfect substitutes, imperfect substitutes, and perfect substitutes with time-variable rates of substitution based on a cooperative reward system. Simulations of a highway scenario reveal the differences in recurring situations: Perfect substitutes indeed maximize total utility, but at the expense of a highly unequal utility distribution that may lead to poor long-term user acceptance; imperfect substitutes promote an equal utility distribution, but leave much of the potential of cooperative behavior unused; introducing a cooperative reward system based on memories of costs is shown to allow for a trade-off between both - altruistic-cooperative behavior without constant preference of one agent over the other, which is assumed to improve user acceptance.
基于合作奖励制度的高级合作分散决策
代理可以从合作行为中获益,因为它的目的是增加总效用。在交通情况下,一个代理可能通过让步来表现合作。在反复出现的情况下,这可能导致利益分配不平衡。然而,比起不平衡的效用分配,人类更喜欢均衡的效用分配。最先进的合作分散决策可能会导致这种不平衡的效用分配,而先进的合作分散决策可以支持代理之间的平等。比较了三种不同的方法:考虑代理人效用的完全替代、不完全替代和基于合作奖励制度的时变替代率的完全替代。高速公路情景的模拟揭示了反复出现的情况的差异:完全替代确实使总效用最大化,但代价是效用分配高度不平等,这可能导致用户长期接受度较差;不完全替代促进了平等的效用分配,但使合作行为的大部分潜力未被利用;引入基于成本记忆的合作奖励系统被证明允许在两者之间进行权衡-利他-合作行为,而不需要一个代理对另一个代理的持续偏好,这被认为可以提高用户的接受度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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