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 timeslots 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.

Human social hierarchy has the unique characteristic of existing in two forms. Firstly, as an informal hierarchy where leaders and followers are implicitly defined by their personal characteristics, and secondly, as an institutional hierarchy where leaders and followers are explicitly appointed by group decision. Although both forms can reduce the time spent in organising collective tasks, institutional hierarchy imposes additional costs. It is therefore natural to question why it emerges at all. The key difference lies in the fact that institutions can create hierarchy with only a single leader, which is unlikely to occur in unregulated informal hierarchy. To investigate if this difference can affect group decision-making and explain the evolution of institutional hierarchy, we first build an opinion-formation model that simulates group decision making. We show that in comparison to informal hierarchy, a single-leader hierarchy reduces (i) the time a group spends to reach consensus, (ii) the variation in consensus time, and (iii) the rate of increase in consensus time as group size increases. We then use this model to simulate the cost of organising a collective action which produces resources, and integrate this into an evolutionary model where individuals can choose between informal or institutional hierarchy. Our results demonstrate that groups evolve preferences towards institutional hierarchy, despite the cost of creating an institution, as it provides a greater organisational advantage which is less affected by group size and inequality.

Hierarchy is an efficient way for a group to organize, but often goes along with inequality that benefits leaders. To control despotic behaviour, followers can assess leaders’ decisions by aggregating their own and their neighbours’ experience, and in response challenge despotic leaders. But in hierarchical social networks, this interactional justice can be limited by (i) the high influence of a small clique who are treated better, and (ii) the low connectedness of followers. Here we study how the connectedness of a social network affects the co-evolution of despotism in leaders and tolerance to despotism in followers. We simulate the evolution of a population of agents, where the influence of an agent is its number of social links. Whether a leader remains in power is controlled by the overall satisfaction of group members, as determined by their joint assessment of the leaders behaviour. We demonstrate that centralization of a social network around a highly influential clique greatly increases the level of despotism. This is because the clique is more satisfied, and their higher influence spreads their positive opinion of the leader throughout the network. Finally, our results suggest that increasing the connectedness of followers limits despotism while maintaining hierarchy.

The sudden transition from egalitarian groups to hierarchical societies that occurred with the origin of agriculture is one of the most striking features of the evolution of human societies. Hierarchy is reflected by the evolution of an asymmetrical distribution of the influence of individuals. Although the benefits to leaders themselves are easily justified, it is still hard to identify the causes for the evolution of exploited followers. However, leaders also play an important role in solving coordination problems, a role which would have been amplified by the increase in group size induced by the advent of agriculture. Can this lead to the emergence of leadership directly from the evolution of traits affecting individual influence in group decisions? This question is yet unanswered mainly because of a lack of a mechanistic model linking individual influence to group productivity. Here we fill this gap by explicitly describing the organization of group by a decision-making process. We have developed an evolutionary model where individuals organize to carry out a collective task that produces surplus resources. These surplus resources then drive a demographic expansion of group size. Our results show that a stable distribution of leaders and followers can emerge from the evolution of traits affecting individual influence in decision making, even in the presence of inequality. In addition, our model highlights the conditions and dynamics underlying the development of hierarchy. In line with theoretical work on the evolutionary origins of leadership, this model contributes to understanding the interactions between individual evolution and social structure.

Artificial Life is concerned with understanding the dynamics of human societies. A defining feature of any human society is its institutions. However, defining exactly what an institution is has proven difficult, with authors often talking past each other. This paper presents a dynamic model of institutions, which views institutions as political game forms that generate the rules of a groups economic interactions. Unlike much prior work, the framework presented in this paper allows for the construction of explicit models of the evolution of institutional rules. It takes account of the fact that group members are likely to try to actively create institutional rules that benefit themselves at the expense of others. The paper finishes with an explicit example of how a model of the evolution of institutional rewards and punishment for promoting cooperation can be created. It is intended that this framework will allow Artificial Life researchers to address how human groups can create conditions that support cooperation. This will help to both provide a better understanding of historical human social evolution, and help in understanding the resolution of pressing public goods problems such as climate change.