Agent-based Models as Fictive Instantiations of Ecological Processes
Philosophy and Theory in Biology
It has been argued that problems in computer simulation bear enough resemblance to recognized issues in the philosophy of modeling that they only pose philosophical challenges analogous to those found in standard analytic models used to represent the natural world. Agent-based models have become important for understanding the interactions among organisms in ecological and evolutionary systems. Like the complexity found in natural systems, these models allow emergent patterns to arise from
... to arise from lower-level processes. The use of these models presents several philosophical problems to understanding how a simulation represents and what role it can play in scientific discourse. One fruitful way to look at agent-based models is as instantiations: a representational mode that recreates a type of the system with which one is working. I explore whether agent-based models present new challenges for philosophy of science and why these types of models are relevant for understanding emergent systems. I argue that certain types of ecological systems may be examined more substantively with agential models. I also suggest that these models might be described as fictions and require deeper hermeneutic engagement than non-simulation models. KEYWORDS Agent-based models • Ecological modeling • Instantiations • Models as fictions • Philosophy of simulation Philos Theor Biol (2012) 4:e303 OPEN ACCESS -Freely Available at philosophyandtheoryinbiology.org PECK -AGENT-BASED MODELS 2 OPEN ACCESS -Freely Available at philosophyandtheoryinbiology.org In this paper I weigh in on some of these issues and elaborate why I think that agent-based ecological simulations are more complicated, and more interesting. I will focus on three things. First, I suggest that a fruitful way to look at agent-based models is as instantiations: a representational mode that recreates the type of the system with which one is working. Rather than a representation based upon mathematical or pictorial description, an instantiation recreates, in part, that same system with objects that have formal attributes similar to those found in the target system. Second, I explore whether agent-based models present new problems for philosophy of science and why these types of models will be relevant for understanding emergent systems. I argue that certain types of ecological systems may be examined more substantively with agential models (Odenbaugh 2005b; De Roos and Persson 2005) . Third, I highlight that these models require a deeper hermeneutic engagement than analytic models. Current discussions within philosophy of science that fruitfully critique models as fictions offer a helpful perspective for better understanding these types of systems. These viewpoints may be useful for simulations of various types and across different disciplines, but my focus will be on agent-based ecological models. I show that these models pose many novel and challenging issues that require new conceptual work by philosophers of science. A few preliminaries on ecological theories Before we talk about agent-based simulation in ecology, there are some things about ecology to keep in mind. Ecological systems are arguably among the most complex systems found in nature. They often rival the complexity of such multidimensional and challenging sciences as developmental biology and neuroscience. The reasons for ecology's complexity are multifarious. First, ecological systems are hierarchical, with higher-level processes constraining and influencing lowerlevels, and, in turn, lower-level processes contributing to the structure and function of higher-levels. These multiple scales of interaction can lead to complicated dynamics. Second, ecological systems are numerically complex; they are comprised of a large number of players in networks of interacting organisms, which structure and are structured by many abiotic elements. Food webs, competitive interactions among and within species, structural dynamics of the physical environment produced by both abiotic and biotic influences, animal behavior and all this entails, are just a few pieces of the composite environmental milieu. For example, soils and plant community composition can be dramatically influenced by differences in solar energy shaped by the topology of landscape-level factors. Third, ecological systems are historical in nature. They are contingent on accidents of colonization by differing organisms, accidents of weather and climate, perturbations caused by natural and human processes, and other influences that affect the historical development of an ecosystem. This contingency is the result of a complex evolutionary history in which species have evolved and coevolved over millions of years, creating interdependencies, reliances, mutualisms, and other symbiotic relationships that structure ecological communities. Fourth, the part-whole relationships of ecosystem components are a fundamental aspect of these systems, even though in many ways they are contingent and accidental. The species present form relationships with other components, but do not have functional relationships to the 'whole' in the same way that the components of organisms do. The predator's regulation of prey does not serve as a function toward some ecosystem goal in the same way that a predator's heart functions toward pumping blood. This is because ecosystems as a whole are not evolved structures in the same sense that organisms are. However, ecosystems do have tendencies and capacities. For example, grassland or wetland ecosystems seem to function similarly in many parts of the world despite being composed of different species of plants, animals, and soil organisms. In short, ecosystems are complex spatially, temporally, and hierarchically. They also have numerous contingent features due to history and geography. These features have fostered the argument that there may be no laws in ecology and that ceteris paribus conditions dominate, if not swamp, most aspects of ecological systems (Cooper 2003) . Ecological theory has been hard to come by and, when proposed, tends to be ecosystem, species, or location specific. Many instances are so general or even cartoonish-like the 'law' of exponential growth-that they are hard to apply to actual organisms in real ecosystems except in broadest outline (Hall 1988) . Ecology has proven to be a theory-poor science. Even recent attempts at providing unifying concepts seem limited and only ACKNOWLEDGMENTS I would like to thank Stephen Downes, Anya Plutynski, and Eric Winsberg for reading earlier drafts of this paper and providing helpful suggestions and insights. I would also like to thank the participants in the MS4 Simulation Conference in Toronto, CA for the insights and discussions that helped improve this paper significantly.