1271 lines
50 KiB
TeX
1271 lines
50 KiB
TeX
%% C2S 2026 Keynote — Simon Carrignon
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%% Computational Cultural Science Workshop, Paris, 18--19 May 2026
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%% École nationale des Chartes -- PSL
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%% Compile with: lualatex slides-c2s-2026.tex
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\vskip1.5pt
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\begin{columns}
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\hspace{.3cm}
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\column{.22\paperwidth}
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\textbf{Simon Carrignon} · UCL GEE \hspace{.1cm}\textbf{|}
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\column{.45\paperwidth}
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\insertsectionnavigationhorizontal{.40\textwidth}{}{\hskip0pt}%
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\hspace{.1cm}\textbf{|}
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\column{.18\paperwidth}
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\textbf{C2S Paris · May 2026}
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\column{.12\paperwidth}
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%% ── Title info ──────────────────────────────────────────────────────────
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\title{%
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\textbf{\large Bridging Scales in Cultural Evolution:\\
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Computational Models, Archaeological Data, and Machine Learning}}
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\author{%
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\textcolor{white}{%
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Simon Carrignon (\href{mailto:s.carrignon@ucl.ac.uk}{s.carrignon@ucl.ac.uk})\\
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University College London -- Dept.\ of Genetics, Evolution \& Environment\\[4pt]
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ERC COREX Project
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}
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}
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\institute{}
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\date{%
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\textcolor{white}{%
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C2S --- Computational Cultural Science Workshop\\
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École nationale des Chartes -- PSL, Paris\\
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18--19 May 2026
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}
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}
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%% ═══════════════════════════════════════════════════════════════════════════
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\begin{document}
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%% ── Title Slide ─────────────────────────────────────────────────────────
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\begingroup
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\setbeamertemplate{footline}{}
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\setbeamercolor{background canvas}{bg=ifsapurple,fg=white}
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\frame[plain]{\titlepage}
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\setbeamercolor{background canvas}{bg=}
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\endgroup
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%% ── Plan Slide ──────────────────────────────────────────────────────────
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\begin{frame}{Plan}
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\begin{itemize}[<+->]
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\item Introduction --- Cultural Evolution \& Computational Approaches
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\item Computational Models --- ABM, Cultural Transmission, 4-Box Model
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\item Archaeological Evidence --- The Record, Its Biases, What It Gives Us
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\item ML on Archaeological Data --- Autoencoder on Faunal Remains
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\item Approximate Bayesian Computation --- Coupling Data \& Models
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\item Conclusion \pause --- Open Questions \& Connections to CCS
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\end{itemize}
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\end{frame}
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%% ═══════════════════════════════════════════════════════════════════════════
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\section{Introduction}
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\sectiondivider{Introduction}
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%% ── What is Cultural Evolution? ─────────────────────────────────────────
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\begin{frame}{Cultural Change}
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``Information, traditions, behaviours transmitted socially
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(via direct or indirect interactions with peers)''
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\vspace{6pt}
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\begin{itemize}[<+->]
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\item Languages, technologies, artistic styles, subsistence strategies\ldots
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\item \textbf{Changes of frequencies} of cultural variants over time
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\item Analogous to biological evolution --- but with distinct mechanisms
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\end{itemize}
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\vspace{8pt}
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\uncover<4->{%
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\begin{center}
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\begin{tikzpicture}[
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icon/.style={draw=ifsapurple, rounded corners=3pt, minimum size=1.2cm,
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align=center, font=\scriptsize, fill=purplelight, line width=0.6pt}
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]
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\node[icon] (a) at (0,0) {words};
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\node[icon] (b) at (2.5,0) {pottery};
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\node[icon] (c) at (5,0) {tools};
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\node[icon] (d) at (7.5,0) {food\\practices};
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\node[icon] (e) at (10,0) {digital\\culture};
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\end{tikzpicture}
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\end{center}
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}
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\end{frame}
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%% ── Understanding Cultural Change ───────────────────────────────────────
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\begin{frame}{Understanding Cultural Change}
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\uncover<+->{What drives these changes?}
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\begin{columns}[t]
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\column{.50\textwidth}
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\vspace{4pt}
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\begin{itemize}[<+->]
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\item Environmental pressures
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\item Social network structure
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\item Cognitive biases \& learning strategies
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\item Demographic processes
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\end{itemize}
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\column{.50\textwidth}
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\uncover<6->{%
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At relatively large geographical \emph{\&} temporal scales:
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\vspace{4pt}
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\begin{itemize}
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\item Limited applicability of general theories
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\item Limited use of experiments
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\item Limited/noisy/biased empirical evidence
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\end{itemize}
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\vspace{6pt}
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\textbf{How to study meso-scale cultural evolution?}
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}
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\end{columns}
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\end{frame}
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%% ── The COREX Project ───────────────────────────────────────────────────
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\begin{frame}{The COREX Project (ERC)}
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\begin{columns}[T]
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\begin{column}{0.55\textwidth}
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\textbf{CO}mputational \textbf{R}esearch on Cultural \textbf{E}volution
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\textbf{X}-disciplinary
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\vspace{8pt}
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\begin{itemize}[<+->]
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\item ERC-funded project at UCL (Dept.\ GEE)
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\item Studying cultural evolution through \textbf{computational}
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and \textbf{archaeological} approaches
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\item Integrating agent-based models, ML, and Bayesian inference
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with large archaeological databases
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\item Focus on subsistence strategies, material culture,
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and demographic dynamics
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\end{itemize}
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\end{column}
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\begin{column}{0.42\textwidth}
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\pause
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\begin{block}{Key Data Sources}
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\small
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Faunal assemblages\\
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Isotope data, ${}^{14}$C dates\\
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Ancient DNA\\
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Material culture typologies
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\end{block}
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\vspace{6pt}
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\begin{exampleblock}{Collaborations}
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\small
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ENCOUNTER (Cambridge)\\
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DySoC (UTK)\\
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BIAD consortium
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\end{exampleblock}
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\end{column}
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\end{columns}
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\end{frame}
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%% ── Bridging Scales ─────────────────────────────────────────────────────
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\begin{frame}{Bridging Scales}
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\begin{center}
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\begin{tikzpicture}[
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box/.style={draw=ifsapurple, rounded corners=5pt, minimum height=1.6cm,
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text width=3cm, align=center, font=\small, line width=0.8pt},
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arr/.style={-{Stealth[length=5pt]}, thick, ifsapurple!60, line width=1pt},
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bigarr/.style={-{Stealth[length=6pt]}, very thick, accentred, line width=1.5pt}
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]
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% Local
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\node[box, fill=purplelight] (local) at (0,0)
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{\textbf{Local}\\Individual\\interactions\\[2pt]\footnotesize ethnography};
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% Meso
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\node[box, fill=accentgold!25, draw=accentgold!80!black, line width=1.4pt]
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(meso) at (5.5,0)
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{\textbf{Mesoscale}\\Regional dynamics\\over millennia\\[2pt]
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\footnotesize\color{accentred} our target};
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% Global
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\node[box, fill=purplelight] (global) at (11,0)
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{\textbf{Global}\\Cross-cultural\\universals\\[2pt]\footnotesize big data};
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% Arrows
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\draw[arr] (local) -- (meso);
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\draw[arr] (global) -- (meso);
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% Bottom label
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\node[font=\footnotesize\itshape, ifsapurple] at (5.5,-1.6)
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{Primary evidence: the \textbf{archaeological record}};
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\end{tikzpicture}
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\end{center}
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\vspace{4pt}
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\pause
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\begin{block}{The approach}
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Model \textbf{local interactions} (ABM) $\to$
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Generate \textbf{regional patterns} $\to$
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Compare with \textbf{empirical data} $\to$
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Constrain \textbf{transmission processes}
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\end{block}
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\end{frame}
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%% ═══════════════════════════════════════════════════════════════════════════
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\section[Models]{Computational Models}
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\sectiondivider{Computational Models}
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%% ── Computational Modelling Overview ────────────────────────────────────
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\begin{frame}{Computational Modelling}
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\begin{columns}[t]
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\column{.60\textwidth}
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\begin{itemize}[<+->]
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\item Model local interactions to explore hypotheses
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at different scales (\textbf{ABM})
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\item Extract empirical patterns
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(Bayesian stats, ML,\ldots)
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\item Test method robustness
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(`tactical simulation')
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\end{itemize}
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\column{.40\textwidth}
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\uncover<2->{%
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\begin{block}{Epstein (2008)}
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\small ``If you didn't grow it,\\you didn't explain it.''
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\end{block}
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}
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\end{columns}
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\end{frame}
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%% ── Agent-Based Modelling ───────────────────────────────────────────────
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\begin{frame}{Agent-Based Modelling}
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\begin{columns}[t]
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\column{.55\textwidth}
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\begin{itemize}[<+->]
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\item Explicitly describe low-level interactions
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\item Formalise, generate, and explore hypotheses
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\item Reproducible and testable descriptions
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\item Flexible: demography, spatial structure,
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multiple transmission pathways
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\end{itemize}
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\column{.45\textwidth}
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\uncover<2->{%
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\begin{center}
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\begin{tikzpicture}[scale=0.7,
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agent/.style={circle, draw=ifsapurple, fill=purplelight,
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minimum size=5mm, inner sep=0pt, font=\tiny\bfseries},
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link/.style={ifsapurple!40, line width=0.6pt}
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]
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% Grid of agents
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\foreach \x/\y/\lab in {0/0/a,1.5/0.3/b,3/0/c,0.5/1.5/d,2/1.8/e,
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3.5/1.5/f,0/3/g,1.5/2.8/h,3/3.2/i} {
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\node[agent] (\lab) at (\x,\y) {};
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}
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% Links
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\foreach \a/\b in {a/b,b/c,a/d,b/e,c/f,d/e,e/f,d/g,e/h,f/i,g/h,h/i} {
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\draw[link] (\a) -- (\b);
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}
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% Highlight a transmission event
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\draw[-{Stealth[length=4pt]}, accentred, thick] (e) -- (h)
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node[midway, right, font=\tiny] {copy};
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% Label
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\node[font=\scriptsize, ifsapurple, below] at (1.5,-0.5)
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{agents on a network};
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\end{tikzpicture}
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\end{center}
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}
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\end{columns}
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\end{frame}
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%% ── The 4-Box Model ────────────────────────────────────────────────────
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\begin{frame}{Cultural Transmission --- The 4-Box Model}
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\begin{columns}[t]
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\column{.45\textwidth}
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\textbf{Vidiella et al.\ (2022):}
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\begin{align*}
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\Pr(i,t{+}1) = \frac{1}{Y_t}\, p_i(t)^{\alert{J}}\, e^{\alert{\beta}\, U_i + \psi}
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\end{align*}
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\begin{itemize}[<+->]
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\item $\alert{J}$: social conformity (frequency dependence)
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\item $\alert{\beta}$: transparency of intrinsic utility
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\end{itemize}
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\uncover<3->{A 2D space to classify cultural change:}
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\column{.55\textwidth}
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\uncover<3->{%
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\begin{center}
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\begin{tikzpicture}[scale=0.85,
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box/.style={draw=ifsapurple, rounded corners=3pt,
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minimum height=1.4cm, text width=2.6cm, align=center,
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font=\scriptsize, line width=0.6pt}
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]
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% Axes
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\draw[-{Stealth[length=5pt]}, thick, ifsapurple]
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(-0.2,0) -- (6.2,0) node[right, font=\small] {$J$ (conformity)};
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\draw[-{Stealth[length=5pt]}, thick, ifsapurple]
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(0,-0.2) -- (0,4.8) node[above, font=\small] {$\beta$ (utility)};
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% Quadrants
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\node[box, fill=purplelight] at (1.5,1.2) {Drift\\(neutral)};
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\node[box, fill=accentgold!20] at (4.5,1.2) {Conformity\\bias};
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\node[box, fill=ifsapurple!12] at (1.5,3.5) {Content\\bias};
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\node[box, fill=accentred!12] at (4.5,3.5) {Guided\\variation};
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% Parameter labels
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\node[font=\tiny, midgray] at (1.5,-0.5) {low $J$};
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\node[font=\tiny, midgray] at (4.5,-0.5) {high $J$};
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\node[font=\tiny, midgray, rotate=90] at (-0.6,1.2) {low $\beta$};
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\node[font=\tiny, midgray, rotate=90] at (-0.6,3.5) {high $\beta$};
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\end{tikzpicture}
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\end{center}
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}
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\end{columns}
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\end{frame}
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%% ── Cultural Transmission Pathways ──────────────────────────────────────
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\begin{frame}{Cultural Transmission Pathways}
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\begin{center}
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\begin{tikzpicture}[
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gen/.style={draw=ifsapurple, rounded corners=2pt, minimum height=0.8cm,
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text width=2.2cm, align=center, font=\scriptsize, fill=purplelight},
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arr/.style={-{Stealth[length=4pt]}, ifsapurple, line width=0.7pt},
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lab/.style={font=\tiny, midgray, align=center}
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]
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% Parent generation
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\node[gen, fill=ifsapurple!20] (p1) at (0,3) {Parent A};
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\node[gen, fill=ifsapurple!20] (p2) at (3,3) {Parent B};
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\node[gen, fill=ifsapurple!12] (elder) at (6,3) {Elder / Peer};
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\node[gen, fill=accentgold!15] (comm) at (9.5,3) {Community};
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% Child
|
|
\node[gen, fill=accentred!12, text width=2.6cm, minimum height=1cm]
|
|
(child) at (4.5,0) {\textbf{Learner}};
|
|
|
|
% Vertical
|
|
\draw[arr, thick] (p1.south) -- (child.north west)
|
|
node[midway, left, lab] {vertical};
|
|
\draw[arr, thick] (p2.south) -- (child.north)
|
|
node[midway, right, lab] {vertical};
|
|
|
|
% Oblique
|
|
\draw[arr, dashed] (elder.south) -- (child.north east)
|
|
node[midway, right, lab] {oblique};
|
|
|
|
% Horizontal
|
|
\draw[arr, dotted, thick] (comm.south) -- (child.east)
|
|
node[midway, right, lab] {horizontal\\(peers)};
|
|
|
|
% Pre/post marital annotation
|
|
\node[font=\scriptsize\itshape, ifsapurple, align=center] at (11.5,1.5)
|
|
{pre- \& post-\\marital pathways};
|
|
\end{tikzpicture}
|
|
\end{center}
|
|
\vspace{4pt}
|
|
\begin{itemize}
|
|
\item<2-> Multiple pathways combine: vertical, oblique, horizontal
|
|
\item<3-> Post-marital resocialisation adds further complexity
|
|
\item<4-> Sex-biased transmission: probability $s$ to copy from female role model
|
|
\end{itemize}
|
|
\end{frame}
|
|
|
|
%% ── Hitchhiking and Migration ───────────────────────────────────────────
|
|
\begin{frame}{Cultural Hitchhiking \& Migration}
|
|
\begin{columns}[T]
|
|
\begin{column}{0.52\textwidth}
|
|
\textbf{Analogy with genetic hitchhiking:}
|
|
\begin{itemize}[<+->]
|
|
\item `Neutral traits' spreading alongside advantageous technology
|
|
\item Dispersal of farming:\\
|
|
demographic growth + cultural contact
|
|
\item Marital rules ($\rho$) modulate which traits hitchhike
|
|
\end{itemize}
|
|
\vspace{4pt}
|
|
\uncover<4->{%
|
|
\begin{block}{Model ingredients}
|
|
\small
|
|
Demography (growth, fission)\\
|
|
Adaptive technology (community-level)\\
|
|
Neutral traits (individual-level, multiple pathways)
|
|
\end{block}
|
|
}
|
|
\end{column}
|
|
\begin{column}{0.45\textwidth}
|
|
\uncover<2->{%
|
|
\begin{center}
|
|
\begin{tikzpicture}[scale=0.65,
|
|
comm/.style={circle, draw=ifsapurple, minimum size=8mm,
|
|
font=\tiny\bfseries, line width=0.6pt},
|
|
farr/.style={-{Stealth[length=4pt]}, ifsapurple!50, line width=0.5pt}
|
|
]
|
|
% Farmer communities
|
|
\node[comm, fill=accentgold!30] (f1) at (0,0) {F};
|
|
\node[comm, fill=accentgold!30] (f2) at (1.5,1) {F};
|
|
% HG communities
|
|
\node[comm, fill=purplelight] (h1) at (3,0) {HG};
|
|
\node[comm, fill=purplelight] (h2) at (4.5,1) {HG};
|
|
\node[comm, fill=purplelight] (h3) at (3,2.2) {HG};
|
|
\node[comm, fill=purplelight] (h4) at (5.5,2.5) {HG};
|
|
% Expansion arrows
|
|
\draw[farr, thick] (f1) -- (h1);
|
|
\draw[farr, thick] (f2) -- (h3);
|
|
\draw[farr, dashed] (h1) -- (h2);
|
|
\draw[farr, dashed] (h3) -- (h4);
|
|
% Label
|
|
\node[font=\tiny\itshape, ifsapurple] at (2.7,-0.8)
|
|
{farming expansion \& cultural contact};
|
|
\end{tikzpicture}
|
|
\end{center}
|
|
}
|
|
\end{column}
|
|
\end{columns}
|
|
\end{frame}
|
|
|
|
|
|
%% ═══════════════════════════════════════════════════════════════════════════
|
|
\section[Evidence]{Archaeological Evidence}
|
|
\sectiondivider{Archaeological Evidence}
|
|
|
|
%% ── What the Record Gives Us ────────────────────────────────────────────
|
|
\begin{frame}{What the Archaeological Record Gives Us}
|
|
\begin{columns}[T]
|
|
\begin{column}{0.50\textwidth}
|
|
\textbf{A unique window into the past:}
|
|
\begin{itemize}
|
|
\item Material traces of human activity
|
|
\item Spatial distributions of artefacts
|
|
\item Typological and technological variation
|
|
\item Covers millennia and all world regions
|
|
\end{itemize}
|
|
\end{column}
|
|
\begin{column}{0.47\textwidth}
|
|
\begin{alertblock}{But deeply imperfect}
|
|
\begin{itemize}
|
|
\item Organic materials lost
|
|
\item Spatial sampling uneven
|
|
\item Temporal resolution coarse
|
|
\item Behaviour $\to$ material $\to$ preservation $\to$ observation
|
|
\end{itemize}
|
|
\end{alertblock}
|
|
\end{column}
|
|
\end{columns}
|
|
\vspace{6pt}
|
|
\pause
|
|
\begin{block}{Key insight}
|
|
Methods must be \textbf{explicitly designed} to account for these filters ---
|
|
not applied naively from other domains
|
|
\end{block}
|
|
\end{frame}
|
|
|
|
%% ── Taphonomic Filter Diagram ───────────────────────────────────────────
|
|
\begin{frame}{The Taphonomic Filter}
|
|
\begin{center}
|
|
\begin{tikzpicture}[
|
|
box/.style={draw, rounded corners=4pt, minimum height=1.6cm,
|
|
text width=2.6cm, align=center, font=\small},
|
|
filt/.style={draw, rounded corners=2pt, fill=accentred!15,
|
|
minimum height=1.6cm, text width=2.2cm, align=center,
|
|
font=\small, thick, draw=accentred},
|
|
arr/.style={-{Stealth[length=5pt]}, thick, ifsapurple, line width=1.2pt}
|
|
]
|
|
% Original signal
|
|
\node[box, fill=ifsapurple!15, draw=ifsapurple] (sig) at (0,0)
|
|
{\textbf{Original}\\cultural\\signal\\[2pt]\footnotesize 100\% diversity};
|
|
|
|
% Preservation filter
|
|
\node[filt] (pres) at (4.2,0)
|
|
{\textbf{Preservation}\\filter\\[2pt]\footnotesize decay, erosion,\\chemistry};
|
|
|
|
% Sampling filter
|
|
\node[filt] (samp) at (8.4,0)
|
|
{\textbf{Sampling}\\filter\\[2pt]\footnotesize excavation,\\recording};
|
|
|
|
% Observed record
|
|
\node[box, fill=accentgold!20, draw=accentgold!80!black] (obs) at (12.6,0)
|
|
{\textbf{Observed}\\record\\[2pt]\footnotesize 5--20\%\\preserved};
|
|
|
|
% Arrows
|
|
\draw[arr] (sig) -- (pres);
|
|
\draw[arr] (pres) -- (samp);
|
|
\draw[arr] (samp) -- (obs);
|
|
|
|
% Loss annotations
|
|
\draw[accentred, thick,
|
|
decorate, decoration={snake, amplitude=2pt, segment length=6pt}]
|
|
(4.2,-1.5) -- ++(0,-0.4);
|
|
\node[below, font=\footnotesize, accentred] at (4.2,-1.9) {material lost};
|
|
\draw[accentred, thick,
|
|
decorate, decoration={snake, amplitude=2pt, segment length=6pt}]
|
|
(8.4,-1.5) -- ++(0,-0.4);
|
|
\node[below, font=\footnotesize, accentred] at (8.4,-1.9) {information lost};
|
|
\end{tikzpicture}
|
|
\end{center}
|
|
\vspace{4pt}
|
|
\pause
|
|
\begin{exampleblock}{Implication}
|
|
Naive diversity estimates from the archaeological record can be
|
|
\textbf{systematically misleading} --- simulation studies show that
|
|
spatial structure and mobility rates interact with taphonomic loss
|
|
\end{exampleblock}
|
|
\end{frame}
|
|
|
|
%% ── Bronze Age Networks (BIAD) ──────────────────────────────────────────
|
|
\begin{frame}{Bronze Age Networks --- The BIAD Project}
|
|
\begin{columns}[T]
|
|
\begin{column}{0.50\textwidth}
|
|
\begin{exampleblock}{Question}
|
|
How were artefacts distributed across Europe, and what does
|
|
network structure tell us about cultural interaction?
|
|
\end{exampleblock}
|
|
\vspace{4pt}
|
|
\begin{itemize}[<+->]
|
|
\item Similarity networks from assemblage data
|
|
\item Community detection $\to$ regional interaction zones
|
|
\item Structure \textbf{not visible} in raw typologies alone
|
|
\end{itemize}
|
|
\end{column}
|
|
\begin{column}{0.47\textwidth}
|
|
\uncover<2->{%
|
|
\begin{center}
|
|
\begin{tikzpicture}[scale=0.7,
|
|
site/.style={circle, draw=ifsapurple, fill=ifsapurple!20,
|
|
minimum size=6mm, font=\tiny\bfseries},
|
|
edge/.style={thick, ifsapurple!50}
|
|
]
|
|
\node[site] (A) at (0,0) {A};
|
|
\node[site] (B) at (2,1.2) {B};
|
|
\node[site] (C) at (4,0.2) {C};
|
|
\node[site] (D) at (2.5,-1) {D};
|
|
\node[site, fill=accentgold!30, draw=accentgold] (E) at (5.5,1) {E};
|
|
\node[site] (F) at (5,-1) {F};
|
|
\node[site, fill=accentgold!30, draw=accentgold] (G) at (7,0) {G};
|
|
\draw[edge, line width=2pt] (A) -- (B);
|
|
\draw[edge, line width=1.5pt] (B) -- (C);
|
|
\draw[edge] (A) -- (D);
|
|
\draw[edge, line width=2pt] (C) -- (D);
|
|
\draw[edge, line width=1.5pt] (C) -- (E);
|
|
\draw[edge] (D) -- (F);
|
|
\draw[edge, line width=2pt] (E) -- (G);
|
|
\draw[edge, line width=1.5pt] (F) -- (E);
|
|
\draw[edge] (F) -- (G);
|
|
\draw[edge] (B) -- (D);
|
|
% Cluster outlines
|
|
\begin{scope}[on background layer]
|
|
\node[draw=ifsapurple!30, rounded corners=8pt, fill=ifsapurple!5,
|
|
fit=(A)(B)(C)(D), inner sep=4pt] {};
|
|
\node[draw=accentgold!50, rounded corners=8pt, fill=accentgold!5,
|
|
fit=(E)(F)(G), inner sep=4pt] {};
|
|
\end{scope}
|
|
\end{tikzpicture}
|
|
\end{center}
|
|
\vspace{2pt}
|
|
\begin{block}{\small Related projects}
|
|
\footnotesize EPNet (Roman economy)\\
|
|
BIAD (Bronze \& Iron Age Database)\\
|
|
bronze-ssr (R/Shiny visualisation)
|
|
\end{block}
|
|
}
|
|
\end{column}
|
|
\end{columns}
|
|
\end{frame}
|
|
|
|
%% ── Merzbach Valley Case Study ──────────────────────────────────────────
|
|
\begin{frame}{Merzbach Valley --- Decorative Motifs}
|
|
\begin{columns}[t]
|
|
\column{.50\textwidth}
|
|
Conformity vs.\ utility-based biases:
|
|
\begin{itemize}[<+->]
|
|
\item LBK pottery decorations in the Merzbach Valley
|
|
\item 8 phases, 36 styles, $\sim$200 years
|
|
\item Can the 4-box model capture the observed patterns?
|
|
\end{itemize}
|
|
\uncover<4->{%
|
|
\vspace{4pt}
|
|
\begin{align*}
|
|
\Pr(i,t{+}1) = \frac{1}{Y_t}\, p_i(t)^{J}\, e^{\beta\, U_i + \psi}
|
|
\end{align*}
|
|
\textit{Where in $(J,\beta)$ space does Merzbach fall?}
|
|
}
|
|
\column{.50\textwidth}
|
|
\uncover<2->{%
|
|
\begin{center}
|
|
\begin{tikzpicture}[scale=0.6]
|
|
% Simplified heatmap-like illustration
|
|
\draw[ifsapurple, thick] (0,0) rectangle (5,4);
|
|
\foreach \y/\lab in {0.5/Phase 1, 1/Phase 2, 1.5/Phase 3,
|
|
2/Phase 4, 2.5/Phase 5, 3/Phase 6, 3.5/Phase 7} {
|
|
\node[font=\tiny, left] at (0,\y) {\lab};
|
|
}
|
|
% Bars representing style frequencies
|
|
\foreach \y/\w in {0.5/3.5, 1/3, 1.5/2.8, 2/2.2, 2.5/1.8, 3/1.5, 3.5/1.2} {
|
|
\fill[ifsapurple!40] (0.1,\y-0.15) rectangle (\w,\y+0.15);
|
|
}
|
|
\foreach \y/\w/\s in {0.5/0.5/0.8, 1/0.8/1.5, 1.5/1.2/2,
|
|
2/1.8/2.8, 2.5/2.2/3, 3/2.5/3.5, 3.5/2.8/4} {
|
|
\fill[accentgold!50] (\w+0.2,\y-0.15) rectangle (\s,\y+0.15);
|
|
}
|
|
\node[font=\scriptsize, ifsapurple] at (2.5,-0.5)
|
|
{style frequency by phase};
|
|
\end{tikzpicture}
|
|
\end{center}
|
|
}
|
|
\end{columns}
|
|
\end{frame}
|
|
|
|
|
|
%% ═══════════════════════════════════════════════════════════════════════════
|
|
\section[ML]{ML on Archaeological Data}
|
|
\sectiondivider{ML on Archaeological Data}
|
|
|
|
%% ── Autoencoder on Faunal Data ──────────────────────────────────────────
|
|
\begin{frame}{Autoencoder on Zooarchaeological Data}
|
|
\begin{columns}[T]
|
|
\begin{column}{0.52\textwidth}
|
|
\textbf{New work (COREX):}
|
|
\begin{itemize}[<+->]
|
|
\item Faunal assemblage data: taxon presence/absence
|
|
or frequency matrices across sites
|
|
\item Apply an \textbf{autoencoder} to learn latent dimensions
|
|
\item Compressed representation reveals
|
|
\textbf{cultural and environmental signatures}
|
|
\item Downstream use: summary statistics for ABC,
|
|
input features for ABM calibration
|
|
\end{itemize}
|
|
\end{column}
|
|
\begin{column}{0.46\textwidth}
|
|
\uncover<2->{%
|
|
\begin{block}{Why autoencoders?}
|
|
\small
|
|
Non-linear dimensionality reduction\\[3pt]
|
|
Learn structure without supervision\\[3pt]
|
|
Latent space amenable to\\
|
|
statistical comparison with\\
|
|
simulated outputs
|
|
\end{block}
|
|
}
|
|
\end{column}
|
|
\end{columns}
|
|
\end{frame}
|
|
|
|
%% ── Autoencoder Architecture Diagram ────────────────────────────────────
|
|
\begin{frame}{Autoencoder Architecture}
|
|
\begin{center}
|
|
\begin{tikzpicture}[
|
|
neuron/.style={circle, draw=ifsapurple, minimum size=5mm,
|
|
line width=0.6pt, inner sep=0pt},
|
|
input/.style={neuron, fill=ifsapurple!15},
|
|
hidden/.style={neuron, fill=purplemid!30},
|
|
latent/.style={neuron, fill=accentgold!40, minimum size=7mm,
|
|
line width=1pt, draw=accentgold!80!black},
|
|
output/.style={neuron, fill=ifsapurple!15},
|
|
conn/.style={ifsapurple!30, line width=0.4pt},
|
|
brace/.style={decorate, decoration={brace, amplitude=5pt}, ifsapurple}
|
|
]
|
|
% Input layer (taxa)
|
|
\foreach \i in {1,...,6} {
|
|
\node[input] (i\i) at (0, 4.2-0.7*\i) {};
|
|
}
|
|
\node[font=\tiny, ifsapurple] at (0, 4.6) {\textbf{Input}};
|
|
\node[font=\tiny, midgray] at (0, 0.3) {$n$ taxa};
|
|
|
|
% Encoder hidden
|
|
\foreach \i in {1,...,4} {
|
|
\node[hidden] (e\i) at (2.5, 3.5-0.8*\i) {};
|
|
}
|
|
\node[font=\tiny, ifsapurple] at (2.5, 4.6) {\textbf{Encoder}};
|
|
|
|
% Latent
|
|
\foreach \i in {1,...,2} {
|
|
\node[latent] (z\i) at (5, 2.45-0.9*\i) {};
|
|
}
|
|
\node[font=\scriptsize, accentgold!80!black, above] at (5, 2.2)
|
|
{\textbf{Latent $\mathbf{z}$}};
|
|
|
|
% Decoder hidden
|
|
\foreach \i in {1,...,4} {
|
|
\node[hidden] (d\i) at (7.5, 3.5-0.8*\i) {};
|
|
}
|
|
\node[font=\tiny, ifsapurple] at (7.5, 4.6) {\textbf{Decoder}};
|
|
|
|
% Output layer (reconstruction)
|
|
\foreach \i in {1,...,6} {
|
|
\node[output] (o\i) at (10, 4.2-0.7*\i) {};
|
|
}
|
|
\node[font=\tiny, ifsapurple] at (10, 4.6) {\textbf{Output}};
|
|
\node[font=\tiny, midgray] at (10, 0.3) {$\hat{x} \approx x$};
|
|
|
|
% Connections: input -> encoder
|
|
\foreach \i in {1,...,6} {
|
|
\foreach \j in {1,...,4} {
|
|
\draw[conn] (i\i) -- (e\j);
|
|
}
|
|
}
|
|
% encoder -> latent
|
|
\foreach \i in {1,...,4} {
|
|
\foreach \j in {1,...,2} {
|
|
\draw[conn] (e\i) -- (z\j);
|
|
}
|
|
}
|
|
% latent -> decoder
|
|
\foreach \i in {1,...,2} {
|
|
\foreach \j in {1,...,4} {
|
|
\draw[conn] (z\i) -- (d\j);
|
|
}
|
|
}
|
|
% decoder -> output
|
|
\foreach \i in {1,...,4} {
|
|
\foreach \j in {1,...,6} {
|
|
\draw[conn] (d\i) -- (o\j);
|
|
}
|
|
}
|
|
|
|
% Braces
|
|
\draw[brace] (-0.5,0.7) -- (-0.5,4) node[midway, left, font=\tiny,
|
|
xshift=-6pt, align=right] {taxa freq.\\per site};
|
|
\draw[brace] (10.5,4) -- (10.5,0.7) node[midway, right, font=\tiny,
|
|
xshift=6pt, align=left] {reconstructed\\frequencies};
|
|
\end{tikzpicture}
|
|
\end{center}
|
|
\vspace{2pt}
|
|
\begin{columns}[t]
|
|
\column{.50\textwidth}
|
|
\footnotesize
|
|
\textbf{Input:} taxon frequency matrix ($n_{\text{sites}} \times n_{\text{taxa}}$)
|
|
\column{.50\textwidth}
|
|
\footnotesize
|
|
\textbf{Latent $z$:} compressed representation usable as summary statistics
|
|
\end{columns}
|
|
\end{frame}
|
|
|
|
%% ── Latent Space Exploration ────────────────────────────────────────────
|
|
\begin{frame}{Latent Space --- What It Reveals}
|
|
\begin{columns}[T]
|
|
\begin{column}{0.50\textwidth}
|
|
\textbf{Latent dimensions capture:}
|
|
\begin{itemize}[<+->]
|
|
\item Environmental gradients\\(climate, biome)
|
|
\item Cultural signatures\\(subsistence strategies)
|
|
\item Temporal trends\\(shifts in animal exploitation)
|
|
\end{itemize}
|
|
\vspace{6pt}
|
|
\uncover<4->{%
|
|
\begin{block}{Advantage over PCA}
|
|
\small Non-linear: captures interactions
|
|
between taxa that linear methods miss
|
|
\end{block}
|
|
}
|
|
\end{column}
|
|
\begin{column}{0.47\textwidth}
|
|
\uncover<2->{%
|
|
\begin{center}
|
|
\begin{tikzpicture}[scale=0.75]
|
|
% Axes
|
|
\draw[-{Stealth[length=4pt]}, ifsapurple]
|
|
(-0.3,0) -- (5.5,0) node[right, font=\scriptsize] {$z_1$};
|
|
\draw[-{Stealth[length=4pt]}, ifsapurple]
|
|
(0,-0.3) -- (0,4.5) node[above, font=\scriptsize] {$z_2$};
|
|
|
|
% Cluster 1: pastoralist
|
|
\fill[ifsapurple!15, rounded corners=6pt]
|
|
(0.3,2.5) rectangle (2.2,4.2);
|
|
\node[font=\tiny, ifsapurple] at (1.25,4.5) {pastoralist};
|
|
\foreach \x/\y in {0.6/3, 0.9/3.5, 1.3/2.8, 1.5/3.7, 1.8/3.2} {
|
|
\fill[ifsapurple] (\x,\y) circle (2pt);
|
|
}
|
|
|
|
% Cluster 2: mixed farming
|
|
\fill[accentgold!15, rounded corners=6pt]
|
|
(2.5,0.5) rectangle (4.5,2.5);
|
|
\node[font=\tiny, accentgold!80!black] at (3.5,2.8) {mixed farming};
|
|
\foreach \x/\y in {2.8/1, 3.2/1.5, 3.5/0.8, 3.8/1.8, 4.1/1.2} {
|
|
\fill[accentgold!80!black] (\x,\y) circle (2pt);
|
|
}
|
|
|
|
% Cluster 3: hunter-gatherer
|
|
\fill[accentred!10, rounded corners=6pt]
|
|
(3.5,3) rectangle (5.2,4.3);
|
|
\node[font=\tiny, accentred] at (4.35,4.5) {hunter-gatherer};
|
|
\foreach \x/\y in {3.8/3.3, 4.2/3.8, 4.5/3.5, 4.8/3.9} {
|
|
\fill[accentred] (\x,\y) circle (2pt);
|
|
}
|
|
\end{tikzpicture}
|
|
\end{center}
|
|
\vspace{2pt}
|
|
\footnotesize\itshape Schematic: sites in learned latent space,
|
|
coloured by subsistence strategy
|
|
}
|
|
\end{column}
|
|
\end{columns}
|
|
\end{frame}
|
|
|
|
|
|
%% ═══════════════════════════════════════════════════════════════════════════
|
|
\section[ABC]{Approximate Bayesian Computation}
|
|
\sectiondivider{Approximate Bayesian Computation}
|
|
|
|
%% ── ABC Overview ────────────────────────────────────────────────────────
|
|
\begin{frame}{Approximate Bayesian Computation}
|
|
\textbf{Linking models \& patterns:}
|
|
\begin{itemize}[<+->]
|
|
\item Goal: estimate $P(\theta \mid \text{data})$ --- the posterior
|
|
distribution of model parameters given observed evidence
|
|
\item Likelihood intractable for complex ABMs
|
|
\item ABC: simulate from prior, compare summary statistics,
|
|
accept parameters that produce ``close enough'' output
|
|
\item Computationally costly but \textbf{flexible}
|
|
\end{itemize}
|
|
\end{frame}
|
|
|
|
%% ── ABC Pipeline Diagram ────────────────────────────────────────────────
|
|
\begin{frame}{The ABC Pipeline}
|
|
\begin{center}
|
|
\begin{tikzpicture}[
|
|
box/.style={draw=ifsapurple, rounded corners=4pt, minimum height=1.3cm,
|
|
text width=2.4cm, align=center, font=\small, line width=0.7pt},
|
|
arr/.style={-{Stealth[length=5pt]}, thick, ifsapurple, line width=1.2pt},
|
|
decision/.style={draw=accentred, diamond, aspect=1.8, inner sep=1pt,
|
|
font=\scriptsize, fill=accentred!10, line width=0.7pt, align=center}
|
|
]
|
|
% Empirical data
|
|
\node[box, fill=ifsapurple!15] (data) at (0,0)
|
|
{\textbf{Empirical}\\data\\[2pt]\footnotesize assemblages};
|
|
|
|
% Summary stats (observed)
|
|
\node[box, fill=purplelight] (sobs) at (0,-2.8)
|
|
{\textbf{Summary}\\statistics\\[2pt]\footnotesize $S_{\text{obs}}$};
|
|
|
|
% Prior
|
|
\node[box, fill=accentgold!20] (prior) at (5,0)
|
|
{\textbf{Prior}\\$\pi(\theta)$\\[2pt]\footnotesize parameter space};
|
|
|
|
% Simulation
|
|
\node[box, fill=accentgold!30] (sim) at (5,-2.8)
|
|
{\textbf{Simulate}\\ABM\\[2pt]\footnotesize $S_{\text{sim}}$};
|
|
|
|
% Distance
|
|
\node[decision] (dist) at (9,-1.4)
|
|
{$d(S_{\text{obs}}, S_{\text{sim}})$\\$< \epsilon$ ?};
|
|
|
|
% Posterior
|
|
\node[box, fill=softgreen!20, draw=softgreen!80!black] (post) at (12.5,-1.4)
|
|
{\textbf{Posterior}\\$P(\theta|\text{data})$};
|
|
|
|
% Arrows
|
|
\draw[arr] (data) -- (sobs);
|
|
\draw[arr] (prior) -- (sim);
|
|
\draw[arr] (sobs.east) -- ++(1,0) |- (dist.west);
|
|
\draw[arr] (sim.east) -- ++(0.5,0) |- (dist.west);
|
|
\draw[arr] (dist) -- (post) node[midway, above, font=\tiny] {accept};
|
|
|
|
% Rejection loop
|
|
\draw[arr, dashed, midgray] (dist.north) -- ++(0,1)
|
|
-| (prior.north) node[pos=0.3, above, font=\tiny\itshape] {reject: resample};
|
|
|
|
% Latent space annotation
|
|
\node[font=\tiny\itshape, ifsapurple, below] at (0,-3.8)
|
|
{or: autoencoder latent $z$};
|
|
\end{tikzpicture}
|
|
\end{center}
|
|
\end{frame}
|
|
|
|
%% ── ABC in Practice ─────────────────────────────────────────────────────
|
|
\begin{frame}{ABC in Practice --- Summary Statistics Matter}
|
|
\begin{columns}[T]
|
|
\begin{column}{0.50\textwidth}
|
|
\textbf{Summary statistics for ABC:}
|
|
\begin{enumerate}[<+->]
|
|
\item Number of unique variants per phase
|
|
\item Simpson's diversity index
|
|
\item Disparity (most vs.\ least popular)
|
|
\item Gini coefficient
|
|
\item Turnover rate
|
|
\item Log-normal fit parameters ($\mu$, $\sigma$)
|
|
\end{enumerate}
|
|
\end{column}
|
|
\begin{column}{0.47\textwidth}
|
|
\uncover<3->{%
|
|
\begin{block}{Random Forest Adjustment}
|
|
\small
|
|
Use Random Forest to combine\\
|
|
all summary dimensions\\[3pt]
|
|
$\to$ No need to select metrics\\
|
|
$\to$ Rank/compare metrics\\
|
|
$\to$ Better posterior estimates
|
|
\end{block}
|
|
\vspace{4pt}
|
|
\begin{alertblock}{Key challenge}
|
|
\small Simulated data must be \textbf{transformed}
|
|
to match taphonomic filters before comparison
|
|
\end{alertblock}
|
|
}
|
|
\end{column}
|
|
\end{columns}
|
|
\end{frame}
|
|
|
|
%% ── Tactical Simulation ─────────────────────────────────────────────────
|
|
\begin{frame}{Tactical Simulation --- Validating the Pipeline}
|
|
\begin{columns}[T]
|
|
\begin{column}{0.50\textwidth}
|
|
\textbf{Can we recover known parameters?}
|
|
\begin{itemize}[<+->]
|
|
\item Generate artificial data with known $(J, \beta)$
|
|
\item Apply taphonomic transformation
|
|
\item Run ABC pipeline
|
|
\item Check: does the posterior recover the truth?
|
|
\end{itemize}
|
|
\vspace{4pt}
|
|
\uncover<5->{%
|
|
\textbf{Result:} Yes --- under realistic conditions,
|
|
ABC with RF adjustment recovers planted parameters
|
|
}
|
|
\end{column}
|
|
\begin{column}{0.47\textwidth}
|
|
\uncover<3->{%
|
|
\begin{center}
|
|
\begin{tikzpicture}[scale=0.7]
|
|
% Posterior density sketch
|
|
\draw[-{Stealth[length=4pt]}, ifsapurple]
|
|
(-0.3,0) -- (5.5,0) node[right, font=\scriptsize] {$J$};
|
|
\draw[-{Stealth[length=4pt]}, ifsapurple]
|
|
(0,-0.3) -- (0,3.5) node[above, font=\scriptsize] {density};
|
|
|
|
% Prior (flat)
|
|
\draw[midgray, dashed, line width=0.8pt] (0.2,0.5) -- (5,0.5)
|
|
node[right, font=\tiny] {prior};
|
|
|
|
% Posterior (peaked)
|
|
\draw[ifsapurple, thick, line width=1.2pt]
|
|
plot[smooth, tension=0.7] coordinates
|
|
{(0.2,0.1) (1,0.3) (1.8,1.2) (2.5,2.8) (3.2,1.5) (4,0.4) (5,0.1)};
|
|
\node[font=\tiny, ifsapurple] at (4.2,2) {posterior};
|
|
|
|
% True value
|
|
\draw[accentred, thick, dashed] (2.5,0) -- (2.5,3)
|
|
node[above, font=\tiny, accentred] {true $J$};
|
|
\end{tikzpicture}
|
|
\end{center}
|
|
\vspace{2pt}
|
|
\footnotesize\itshape Schematic: posterior distribution
|
|
concentrates around the true parameter value
|
|
}
|
|
\end{column}
|
|
\end{columns}
|
|
\end{frame}
|
|
|
|
%% ── Connecting Autoencoder + ABC ────────────────────────────────────────
|
|
\begin{frame}{Connecting ML and ABC}
|
|
\begin{center}
|
|
\begin{tikzpicture}[
|
|
box/.style={draw=ifsapurple, rounded corners=5pt, minimum height=1.4cm,
|
|
text width=2.8cm, align=center, font=\small, line width=0.8pt},
|
|
arr/.style={-{Stealth[length=5pt]}, thick, ifsapurple, line width=1.3pt}
|
|
]
|
|
% Data
|
|
\node[box, fill=ifsapurple!15] (data) at (0,0)
|
|
{\textbf{Faunal}\\
|
|
\textbf{assemblages}\\[3pt]
|
|
\footnotesize taxa $\times$ sites};
|
|
|
|
% Autoencoder
|
|
\node[box, fill=purplelight] (ae) at (4.5,0)
|
|
{\textbf{Autoencoder}\\[3pt]
|
|
\footnotesize latent $z$ =\\
|
|
summary stats};
|
|
|
|
% ABM
|
|
\node[box, fill=accentgold!25, draw=accentgold!80!black] (abm) at (9,0)
|
|
{\textbf{ABM}\\
|
|
\textbf{Simulation}\\[3pt]
|
|
\footnotesize cultural\\
|
|
transmission};
|
|
|
|
% ABC
|
|
\node[box, fill=softgreen!15, draw=softgreen!70!black] (abc) at (13,0)
|
|
{\textbf{ABC}\\
|
|
\textbf{Inference}\\[3pt]
|
|
\footnotesize posterior on\\
|
|
$\theta$};
|
|
|
|
% Arrows
|
|
\draw[arr] (data) -- (ae);
|
|
\draw[arr] (ae) -- (abm);
|
|
\draw[arr] (abm) -- (abc);
|
|
|
|
% Feedback
|
|
\draw[arr, dashed, midgray] (abc.south)
|
|
.. controls +(0,-1.5) and +(0,-1.5) .. (abm.south)
|
|
node[midway, below, font=\footnotesize\itshape] {refine};
|
|
\end{tikzpicture}
|
|
\end{center}
|
|
\vspace{6pt}
|
|
\pause
|
|
\begin{block}{The full pipeline}
|
|
Real data $\xrightarrow{\text{autoencoder}}$ latent summary $\xrightarrow{\text{ABC}}$
|
|
posterior on cultural transmission parameters\\[3pt]
|
|
The autoencoder replaces hand-crafted summary statistics
|
|
with \textbf{learned} representations
|
|
\end{block}
|
|
\end{frame}
|
|
|
|
|
|
%% ═══════════════════════════════════════════════════════════════════════════
|
|
\section{Conclusion}
|
|
\sectiondivider{Conclusion}
|
|
|
|
%% ── Summary ─────────────────────────────────────────────────────────────
|
|
\begin{frame}{What We Learned}
|
|
\begin{enumerate}
|
|
\item Cultural evolution at the \textbf{mesoscale} is accessible
|
|
via archaeological evidence + computational methods
|
|
\vspace{5pt}
|
|
\pause
|
|
\item \textbf{Agent-based models} of cultural transmission
|
|
generate testable predictions about drift, selection,
|
|
hitchhiking, and network effects
|
|
\vspace{5pt}
|
|
\pause
|
|
\item \textbf{Machine learning} (autoencoders on faunal data)
|
|
provides summary statistics that capture
|
|
non-linear structure in assemblages
|
|
\vspace{5pt}
|
|
\pause
|
|
\item \textbf{ABC} closes the loop: coupling empirical patterns
|
|
with generative models to estimate transmission parameters
|
|
\vspace{5pt}
|
|
\pause
|
|
\item Taphonomic awareness is \textbf{essential} ---
|
|
methods must account for what the record hides
|
|
\end{enumerate}
|
|
\end{frame}
|
|
|
|
%% ── Open Questions ──────────────────────────────────────────────────────
|
|
\begin{frame}{Open Questions}
|
|
\begin{columns}[T]
|
|
\begin{column}{0.48\textwidth}
|
|
\begin{alertblock}{Validation}
|
|
How do we validate models when\\
|
|
\textbf{ground truth} is unavailable?\\[3pt]
|
|
\footnotesize Tactical simulation, posterior\\
|
|
predictive checks, cross-validation
|
|
\end{alertblock}
|
|
\vspace{4pt}
|
|
\pause
|
|
\begin{alertblock}{Data integration}
|
|
Combining \textbf{heterogeneous} sources:\\
|
|
faunal, isotope, aDNA,\\
|
|
material culture, ${}^{14}$C
|
|
\end{alertblock}
|
|
\end{column}
|
|
\begin{column}{0.48\textwidth}
|
|
\begin{alertblock}{Interpretability}
|
|
ML-extracted patterns must be\\
|
|
\textbf{culturally meaningful},\\
|
|
not just statistically significant
|
|
\end{alertblock}
|
|
\vspace{4pt}
|
|
\pause
|
|
\begin{alertblock}{Scalability}
|
|
Extending the pipeline to\\
|
|
\textbf{larger regions} and\\
|
|
\textbf{longer time spans}\\
|
|
within COREX
|
|
\end{alertblock}
|
|
\end{column}
|
|
\end{columns}
|
|
\end{frame}
|
|
|
|
%% ── Connection to CCS ──────────────────────────────────────────────────
|
|
\begin{frame}{Connections to Computational Cultural Science}
|
|
\begin{block}{The pipeline generalises}
|
|
\textbf{Patterns} $\xrightarrow{\text{extraction}}$
|
|
\textbf{Mechanisms} $\xrightarrow{\text{simulation}}$
|
|
\textbf{Predictions}
|
|
\end{block}
|
|
\vspace{6pt}
|
|
\begin{columns}[T]
|
|
\begin{column}{0.30\textwidth}
|
|
\centering
|
|
\textbf{Any cultural data}\\[4pt]
|
|
\footnotesize
|
|
artefacts · texts\\
|
|
images · networks\\
|
|
digital traces
|
|
\end{column}
|
|
\begin{column}{0.30\textwidth}
|
|
\centering
|
|
\textbf{Generative models}\\[4pt]
|
|
\footnotesize
|
|
ABM · evolutionary\\
|
|
dynamics · diffusion\\
|
|
models
|
|
\end{column}
|
|
\begin{column}{0.30\textwidth}
|
|
\centering
|
|
\textbf{Testable hypotheses}\\[4pt]
|
|
\footnotesize
|
|
transmission rates\\
|
|
drift vs.\ selection\\
|
|
network effects
|
|
\end{column}
|
|
\end{columns}
|
|
\vspace{10pt}
|
|
\pause
|
|
\begin{exampleblock}{If it works on archaeology\ldots}
|
|
\small
|
|
If methods work on the \textbf{hardest} data type
|
|
(fragmented, biased, indirect), they should
|
|
generalise to richer data --- texts, media, digital culture
|
|
\end{exampleblock}
|
|
\end{frame}
|
|
|
|
%% ── Thank You ───────────────────────────────────────────────────────────
|
|
\begingroup
|
|
\setbeamertemplate{footline}{}
|
|
\setbeamercolor{background canvas}{bg=ifsapurple,fg=white}
|
|
\frame[plain,noframenumbering]{%
|
|
\centering
|
|
\textcolor{white}{%
|
|
\vspace{1cm}
|
|
{\Huge\bfseries Thanks!}\\[16pt]
|
|
{\large
|
|
COREX team \& UCL GEE\\[4pt]
|
|
ENCOUNTER team \& McDonald Institute, Cambridge\\[4pt]
|
|
DySoC \& UTK\\[12pt]
|
|
}
|
|
{\normalsize
|
|
\href{mailto:s.carrignon@ucl.ac.uk}{s.carrignon@ucl.ac.uk}\\[6pt]
|
|
\href{https://github.com/simoncarrignon}{github.com/simoncarrignon}\\[12pt]
|
|
}
|
|
{\small\itshape
|
|
C2S --- Computational Cultural Science Workshop\\
|
|
École nationale des Chartes -- PSL · Paris · May 2026
|
|
}
|
|
\vspace{1cm}
|
|
}
|
|
}
|
|
\setbeamercolor{background canvas}{bg=}
|
|
\endgroup
|
|
|
|
%% ═══════════════════════════════════════════════════════════════════════════
|
|
\appendix
|
|
|
|
%% ── Backup: References ──────────────────────────────────────────────────
|
|
\begin{frame}{References}
|
|
\small
|
|
\begin{itemize}
|
|
\item Vidiella, B.\ et al.\ (2022). A cultural evolutionary theory model\ldots
|
|
\textit{Humanities \& Social Sciences Comms.}
|
|
\item Carrignon, S.\ et al.\ (2020). Tableware trade in the Roman East.
|
|
\textit{JASSS} 23(1):3.
|
|
\item Crema, E.R.\ et al.\ (2022). \textit{Rice paddy expansion\ldots}
|
|
\item Epstein, J.M.\ (2008). Why Model? \textit{JASSS} 11(4):12.
|
|
\item Mesoudi, A.\ (2011). \textit{Cultural Evolution.} U.\ Chicago Press.
|
|
\item Bentley, R.A.\ et al.\ (2004). Random drift and culture change.
|
|
\textit{Proc.\ R.\ Soc.\ B} 271:1443--1450.
|
|
\item Deffner, D.\ et al.\ (2024). \textit{Bridging theory and evidence\ldots}
|
|
\end{itemize}
|
|
\end{frame}
|
|
|
|
\end{document}
|