The simplicity of complex agents: a Contextual Action Framework for Computational Agents

Abstract

Collective dilemmas have attracted widespread interest in several social sciences and the humanities including economics, sociology and philosophy. Since Hardin's intuitive example of the Tragedy of the Commons, many real-world public goods dilemmas have been analysed with a wide ranging set of possible and actual solutions. The plethora of solutions to these dilemmas suggests that people make different kinds of decision in different situations. Rather than trying to find a unifying kind of reasoning to capture all situations, as the paradigm of rationality has done, this article develops a framework of agent decision-making for social simulation, that takes seriously both different kinds of decision making as well as different interpretations of situations. The Contextual Action Framework for Computational Agents (CAFCA) allows for the modelling of complex social phenomena, like dilemma situations, with relatively simple agents by shifting complexity from an agent's cognition to an agent's context.

The Addio Pizzo movement: exploring social change using agent-based modelling

“…In the model this is implemented by allowing some extorters to extort but not to punish. This is a reinterpretation of the idea of Fakers from Smith and Varese (2001) which is implemented in Elsenbroich and Badham (2016).…”

“…The model represents entrepreneurs as influenced by normative communication from the state and other entrepreneurs, based on the cognitive normative agent architecture Emil-A (Andrighetto et al (2010)). Elsenbroich and Badham (2016) provides an ABM inspired by the game theoretic analysis of extortion rackets discussed in Smith and Varese (2001). This model shows the importance of implementing social aspects of extortion by comparing a decision-mechanism based only on an entrepreneur's memory with a decision mechanism that takes into account what is happening in the neighbourhood of an entrepreneur.…”

“…The model in this paper contributes to the literature of agent-based models of extortion racketeering by implementing team reasoning, a reasoning mode which takes group membership and group payoffs into account. Team reasoning is a collective extension to individualistic rational reasoning, modelled in Elsenbroich and Badham (2016) and an alternative to normative reasoning modelled in and Nardin et al (2016b), locating the motivation for behaviour change not in the recognition of a social norm but in the membership of a group.…”

“…The purpose of the model is to assist the understanding of the influences of normative and collective considerations together with law enforcement deterrence on levels of acquiescence in extortion racket systems. The model is implemented in NetLogo 5.0.1 (Wilensky (1999)) and is an extension of a basic model assessing the influence of neighbourhood effects on levels of resistance (Elsenbroich and Badham (2016)). This basic model demonstrates that extortion rackets can only become embedded in society if potential victims are able to observe (or otherwise learn about) implemented punishments.…”

“…The baseline reasoning for the model is the individualist strategic mode adopted from the model discussed in Elsenbroich and Badham (2016). Each agent i assesses the punishment probability P i from its neighbourhood, multiplies it by the potential damage caused by a punishment and compares this to the pizzo that will have to be paid (Eq.…”