Resilience through adaptation

Abstract

Adaptation of agents through learning or evolution is an important component of the resilience of Complex Adaptive Systems (CAS). Without adaptation, the flexibility of such systems to cope with outside pressures would be much lower. To study the capabilities of CAS to adapt, social simulations with agent-based models (ABMs) provide a helpful tool. However, the value of ABMs for studying adaptation depends on the availability of methodologies for sensitivity analysis that can quantify resilience and adaptation in ABMs. In this paper we propose a sensitivity analysis methodology that is based on comparing time-dependent probability density functions of output of ABMs with and without agent adaptation. The differences between the probability density functions are quantified by the so-called earth-mover’s distance. We use this sensitivity analysis methodology to quantify the probability of occurrence of critical transitions and other long-term effects of agent adaptation. To test the potential of this new approach, it is used to analyse the resilience of an ABM of adaptive agents competing for a common-pool resource. Adaptation is shown to contribute positively to the resilience of this ABM. If adaptation proceeds sufficiently fast, it may delay or avert the collapse of this system.

Safe Artificial General Intelligence via Distributed Ledger Technology

“…In this manner hacking the blockchain, or attempting to coerce individual consensus agents, would be thwarted in the same way as it is done in the nascent DL methodology extant today. In addition, game theoretic design approaches may help ensure stable evolutionary strategies, likely a succession of them (dynamic equilibrium) [24,53,72]. In that context note there can be no Nash equilibrium with one overwhelmingly dominant player.…”

Safe Artificial General Intelligence via Distributed Ledger Technology

“…In this manner hacking the blockchain, or attempting to coerce individual consensus agents, would be thwarted in the same way as it is done in the nascent DL methodology extant today. In addition, game theoretic design approaches may help ensure stable evolutionary strategies, likely a succession of them (dynamic equilibrium) [24,25,63]. In that context note there can be no Nash equilibrium with one overwhelmingly dominant player.…”

Sensitivity analysis methodologies for analysing emergence using agent-based models

“…Adaptation occurs through natural selection that operates on the agent population level, and typically works through a hereditary mechanism that take place on longer time-scales. This mechanism was considered earlier by Ten Broeke et al (2017). The values of hereditary parameters remain constant over the lifetime of an individual agent, although there is diversity in the values they have for different agents.…”

“…if the value of K is decreased, the available resource may become insufficient to support a stable population of agents. The presence of a hereditary mechanism that allows for adaptation improves the resilience against such tipping points (Ten Broeke et al 2017). Here we will analyse whether these tipping points are affected by the presence of cooperation.…”

“…Given that a decrease in the level of cooperation leads to a strong decrease in population size, the conditions have been chosen such that it is known to be difficult to survive without cooperation (Ten Broeke et al 2017). We change the value of the maximum harvest size R max to modify these assumptions.…”