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Top1. Introduction
The main task of this paper is to generalize the concepts of agency and revealed preference, and we begin by providing a novel definition of what an agent is, at least in an operational sense, further developing the idea of a holonic agent (Marik, McFarlane, & Valckenaers, 2003). Unlike traditional definitions, we assert that nothing we find in the real-world is a perfect agent (Jensen, 1994). Instead, what takes the place of a traditionally defined agent—such as a person or a company—is an entity that only enjoys a limited amount of agency (Ghassem-Aghaee & Oren, 2003). In this sense, the ‘fuzzy’ agents we consider can only be defined in a quantitative, rather than in the traditional qualitative way (Suarez, Rodríguez-Díaz, & Castañón-Puga, 2008), meaning that one can only refer to actors that are more or less of an agent than others, instead of the traditional separation between agents and objects (De Landa, 2006).
Agency, in this work, is a concept that can only be understood in context and is considered to be dispersed holistically across the system. It is therefore referred to as Distributed Agency (DA). The idea behind a framework for describing agency in this way stems from a view of the world in which emergence is pervasive, in which we find gestalts; wholes that are irreducible to their parts and therefore exist in distinct dimensions where different rules apply (Nonaka & Nishiguchi, 2001). In such a world, the independence of events that is assumed in classical statistics theory no longer holds true and a holistic approach is necessary (Crutchfield, 1994; Biggiero, 2001).
In order to appropriately model complex human behavior we must define a canvas in which multiple dimensions of our existence can be defined (Stepney, Polack, & Turner, 2006; Tolk, 2012). Emergent phenomena are ubiquitous in systems that are separated into distinct ontological levels, such as it is in human societies full of consumers, coalitions, families, loyalties, firms, laws, cartels, institutions and governments (Márquez, Castañón-Puga, Castro, & Suarez, 2011). In this sense, our proposal cannot be tied to any one particular model. Instead, the intent is to create a way in which a myriad of non-orthogonal but distinct bodies of knowledge can be expressed in a meta-model of translatable terminology. If we think of a model as a song, then DA could be more accurately compared to a musical staff in which any song can be written than to any particular composition.
While the ultimate aim of this work is to foster the discussion for the development of a common interdisciplinary language to describe multiple levels of reality, the immediate aim is to propose a framework that can be used in the computational description of a multidimensional reality. The rapidly expanding world of the computer simulation—a paradigm with foundations generally related to Multi-Agent Systems (MAS)—is based on independent agents that strategically interact with each other (Van der Hoek & Wooldridge, 2008). The independence granted to the agents in MAS is a computational one, in the sense that each agent processes information internally, without the need to resort to the outside world to draw conclusions about the inputs it receives (for an example of advances in this field, see Zhang, Coleman, Pellon, & Leezer, 2008). In contrast, the proposed DA language allows for a broader computational description of the world, while at the same time allowing for a higher level of realism that the researcher may consider appropriate.