论文标题

促进家庭负载平衡中社会行为的机制

A mechanism to promote social behaviour in household load balancing

论文作者

Brooks, Nathan A., Powers, Simon T., Borg, James M.

论文摘要

减少家庭的峰值能源消耗对于有效使用可再生能源至关重要,以确保可再生能源可以满足家庭需求。这需要散布全天使用高功率电器,例如洗碗机和洗衣机。该问题的传统方法取决于集中公用事业公司设定的差异定价。但是,这种机制并不能有效地促进设备使用情况的广泛转移。在这里,我们考虑了一种替代的分散机制,在该机制中,代理会收到时间段的初始分配以使用其设备,然后可以与其他代理交换。如果代理商愿意在他们接受的交流中更加灵活,那么就所满足的代理时间段偏好的百分比而言,总体满意度将会增加。这需要一种可以激励代理更灵活的机制。在先前的工作的基础上,我们表明一种结合了社会资本的机制 - 对给予和收到的恩惠的跟踪 - 可以激励代理人灵活地采取行动,并通过接受不会立即受益的交流来激发人们的恩惠。我们证明,跟踪的一种有利于代理商的整体满意度的机制,至关重要地允许社会代理人为不受回报有偏见的社会学习而兴奋的自私者提供帮助。因此,即使是完全自私的代理人,也有望学会学会产生社会有益的结果。

Reducing the peak energy consumption of households is essential for the effective use of renewable energy sources, in order to ensure that as much household demand as possible can be met by renewable sources. This entails spreading out the use of high-powered appliances such as dishwashers and washing machines throughout the day. Traditional approaches to this problem have relied on differential pricing set by a centralised utility company. But this mechanism has not been effective in promoting widespread shifting of appliance usage. Here we consider an alternative decentralised mechanism, where agents receive an initial allocation of time-slots to use their appliances and can then exchange these with other agents. If agents are willing to be more flexible in the exchanges they accept, then overall satisfaction, in terms of the percentage of agents time-slot preferences that are satisfied, will increase. This requires a mechanism that can incentivise agents to be more flexible. Building on previous work, we show that a mechanism incorporating social capital - the tracking of favours given and received - can incentivise agents to act flexibly and give favours by accepting exchanges that do not immediately benefit them. We demonstrate that a mechanism that tracks favours increases the overall satisfaction of agents, and crucially allows social agents that give favours to outcompete selfish agents that do not under payoff-biased social learning. Thus, even completely self-interested agents are expected to learn to produce socially beneficial outcomes.

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