We invite papers for a session on complexity science/advanced data analysis/formal modelling at the Theoretical Roman Archaeology Conference (TRAC, Edinburgh, 12-14 April 2018). Please find the abstract below. This is a double session, the first part ‘Exploring Complex Systems’ will focus on finding patters, defining relationships and exploring past complexity, while the second part ‘Understanding Change’ will showcase applications of formal methods to understand social and economic processes and change.
To submit an abstract (300 words), please complete the submission template available here: http://trac.org.uk/events/conferences/trac-2018/
Tom Brughmans, John W. Hanson, Matthew J. Mandich, Iza Romanowska, Xavier Rubio-Campillo
Call for papers, session at Theoretical Roman Archaeology Conference, Edinburgh 12-14 April 2018:
Formal Approaches to Complexity in Roman Archaeology: Exploring Complex Systems and Understanding ChangePart 1: Exploring Complex Systems
Part 2: Understanding Change
Session Organisers: Tom Brughmans (University of Oxford) – John W. Hanson (University of Colorado) – Matthew J. Mandich (University of Leicester) – Iza Romanowska (Barcelona Supercomputing Center) – Xavier Rubio-Campillo (University of Edinburgh)
In recent years archaeologists have increasingly employed innovative approaches used for the study of complex systems to better interpret and model the social, political, and economic structures and interactions of past societies. However, for the majority of Roman archaeologists these approaches remain elusive as a comprehensive review and evaluation is lacking, especially regarding their application in Roman archaeology.In brief, a complex system is made up of many interacting parts (‘components’ or ‘agents’) which form a whole that is more than the sum of its parts – i.e. the interactions of these parts lead to emergent behaviors or outcomes that cannot be (easily) predicted by examining the parts individually. While such systems are characterized by their unpredictable, adaptive, and/or non-linear nature, they are (often) self-organising and governed by observable rules that can be analysed via various methods. For example, many past phenomena, such as urbanism or the functioning of the Roman economy, are complex systems composed of multiple interacting elements and driven by the diverse processes acting upon individuals inhabiting the ancient world. Thus, they can be explored using the approaches and methods of complexity science.The study of complex systems has primarily been undertaken in contemporary settings, in disciplines such as physics, ecology, medicine, and economics. Yet, as the complex nature of ancient civilizations and their similarity to present-day systems is being steadily realized through ongoing analysis, survey, and excavation, archaeologists have now begun to use methods such as scaling studies (e.g. settlement scaling theory), agent-based modeling, and network analyses to approach this complexity. Since these methodologies are designed to examine the interactions and feedback between components within complex systems empirically, they can provide new ways of looking at old data and old problems to supply novel conclusions. However, such methods have only been applied sporadically in ancient settings, and even less so in a Roman context or using Roman archaeological data.Thus, in this two part session we aim to bring these methods, and the Roman archaeologists using them, together by offering a critical review of the theoretical and empirical developments within the study of past complex systems and their interplay with existing ideas, before investigating how we might capitalize on the new opportunities afforded by them in the future. Part I of this session, ‘exploring complex systems’, is concerned with examining and unraveling the underlying structures present in the archaeological record using the formal tools provided by the complex systems framework. Part II, ‘understanding change’, will focus on applications exploring the dynamics of change that generated the patterns observed in existing evidence. In particular, we invite contributions using formal methods including computational modelling and simulation, GIS, and network analyses, as well as diverse theoretical approaches to better understand ancient complex systems.