Computational archaeology

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Computational archaeology describes computer-based analytical methods for the study of long-term human behaviour and behavioural evolution. As with other sub-disciplines that have prefixed 'computational' to their name (e.g., computational biology, computational physics and computational sociology), the term is reserved for (generally mathematical) methods that could not realistically be performed without the aid of a computer.

Computational archaeology may include the use of

The acquisition, documentation and analysis of

Computational archaeology is also known as "archaeological informatics" (Burenhult 2002, Huggett and Ross 2004[6]) or "archaeoinformatics" (sometimes abbreviated as "AI", but not to be confused with artificial intelligence).

Origins and objectives

In recent years, it has become clear that

1. Fundamental research (theoretical AI science) on the structure, properties and possibilities of archaeological data, inference and knowledge building. This includes modeling and managing fuzziness and uncertainty in archaeological data, scale effects, optimal sampling strategies and spatio-temporal effects.
2. Development of computer algorithms and software (applied AI science) that make this theoretical knowledge available to the user.

There is already a large body of literature on the use of quantitative methods and computer-based analysis in archaeology. The development of methods and applications is best reflected in the annual publications of the CAA conference (see external links section at bottom). At least two journals, the Italian Archeologia e Calcolatori and the British Archaeological Computing Newsletter, are dedicated to archaeological computing methods. AI Science contributes to many fundamental research topics, including but not limited to:

• advanced statistics in archaeology, spatial and temporal archaeological data analysis
• bayesian analysis and advanced probability models, fuzziness and uncertainty
  in archaeological data
• scale-related phenomena and scale transgressions
• intrasite analysis (representations of stratigraphy, 3D analysis, artefact distributions)
• landscape analysis (territorial modeling,
  visibility analysis
  )
• optimal
  survey
  and sampling strategies
• process-based modeling and simulation
  models
• archaeological
  heritage management
  applications
• supervised and unsupervised
  classification and typology, artificial intelligence
  applications
• digital
  excavations and virtual reality
• computational reproducibility of archaeological research
• archaeological software development, electronic data sharing and publishing

AI science advocates a formalized approach to archaeological inference and knowledge building. It is

The most important platform for students and researchers in quantitative archaeology and AI science is the international conference on Computer Applications and Quantitative Methods in Archaeology (CAA) which has been in existence for more than 30 years now and is held in a different city of Europe each year. Vienna's city archaeology unit also hosts an annual event that is quickly growing in international importance (see links at bottom).

References