diff --git a/slides-c2s-2026.tex b/slides-c2s-2026.tex index 99a2b11..6f7c9dd 100644 --- a/slides-c2s-2026.tex +++ b/slides-c2s-2026.tex @@ -10,38 +10,54 @@ \usepackage{microtype} \usepackage{booktabs} \usepackage{tikz} +\usetikzlibrary{arrows.meta,positioning,shapes.geometric,calc, + decorations.pathmorphing,fit,backgrounds} \usepackage{xcolor} \usepackage{graphicx} \usepackage{hyperref} -\usepackage{amsmath} +\usepackage{amsmath,amssymb} +\usepackage{appendixnumberbeamer} +\usepackage{multicol} -%% ── Colours (inspired by C2S / PSL palette) ────────────────────────────── -\definecolor{pslblue}{HTML}{003D73} -\definecolor{pslgold}{HTML}{C8A951} -\definecolor{psllight}{HTML}{E8F0F8} -\definecolor{darkgray}{HTML}{333333} -\definecolor{midgray}{HTML}{666666} -\definecolor{accent}{HTML}{C0392B} +%% ── Theme (Goettingen + rose, matching Simon's ref style) ─────────────── +\usetheme[width=0cm]{Goettingen} +\usecolortheme{rose} +\useoutertheme{default} +\setbeamertemplate{navigation 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\textcolor{white!50!ifsapurple}{\insertsectionhead}\hspace{-.2cm}% +} + +%% ── Footer ────────────────────────────────────────────────────────────── \setbeamertemplate{footline}{% - \begin{beamercolorbox}[wd=\paperwidth, ht=2.5ex, dp=1.5ex, leftskip=4mm, rightskip=4mm]{palette primary}% - \tiny Simon Carrignon · UCL GEE \hfill - C2S Workshop, Paris · 18--19 May 2026 \hfill - \insertframenumber/\inserttotalframenumber + \begin{beamercolorbox}[wd=\paperwidth]{footlinecolor}% + \vskip1.5pt + \begin{columns} + \hspace{.3cm} + \column{.22\paperwidth} + \textbf{Simon Carrignon} · UCL GEE \hspace{.1cm}\textbf{|} + \column{.45\paperwidth} + \insertsectionnavigationhorizontal{.40\textwidth}{}{\hskip0pt}% + \hspace{.1cm}\textbf{|} + \column{.18\paperwidth} + \textbf{C2S Paris · May 2026} + \column{.12\paperwidth} + \hfill $\dfrac{\insertframenumber}{\inserttotalframenumber}$\hspace{.3cm} + \end{columns} + \vspace{.1cm} \end{beamercolorbox}% } -%% ── Title info ─────────────────────────────────────────────────────────── -\title{Bridging Scales in Cultural Evolution} -\subtitle{Agent-Based Modelling, Archaeological Patterns,\\and Computational Approaches to Human Cultural Change} -\author{Simon Carrignon} -\institute{% - Department of Genetics, Evolution \& Environment\\ - University College London\\[4pt] - \small CDAL · ENCOUNTER · UGI +%% ── Convenience: section divider command ──────────────────────────────── +\newcommand{\sectiondivider}[1]{% + \begingroup + \setbeamertemplate{footline}{}% + \setbeamercolor{background canvas}{fg=white,bg=ifsapurple}% + \frame[plain,noframenumbering]{\centering\textcolor{white}{\textbf{\Huge #1}}}% + \setbeamercolor{background canvas}{bg=}% + \endgroup } + +%% ── Title info ────────────────────────────────────────────────────────── +\title{% + \textbf{\large Bridging Scales in Cultural Evolution:\\ + Computational Models, Archaeological Data, and Machine Learning}} +\author{% + \textcolor{white}{% + Simon Carrignon (\href{mailto:s.carrignon@ucl.ac.uk}{s.carrignon@ucl.ac.uk})\\ + University College London -- Dept.\ of Genetics, Evolution \& Environment\\[4pt] + ERC COREX Project + } +} +\institute{} \date{% - C2S — Computational Cultural Science Workshop\\ - École nationale des Chartes -- PSL, Paris\\ - 18--19 May 2026 + \textcolor{white}{% + C2S --- Computational Cultural Science Workshop\\ + École nationale des Chartes -- PSL, Paris\\ + 18--19 May 2026 + } } %% ═══════════════════════════════════════════════════════════════════════════ \begin{document} -\maketitle +%% ── Title Slide ───────────────────────────────────────────────────────── +\begingroup +\setbeamertemplate{footline}{} +\setbeamercolor{background canvas}{bg=ifsapurple,fg=white} +\frame[plain]{\titlepage} +\setbeamercolor{background canvas}{bg=} +\endgroup -%% ── Outline ────────────────────────────────────────────────────────────── -\begin{frame}{Outline} - \tableofcontents +%% ── Plan Slide ────────────────────────────────────────────────────────── +\begin{frame}{Plan} + \begin{itemize}[<+->] + \item Introduction --- Cultural Evolution \& Computational Approaches + \item Computational Models --- ABM, Cultural Transmission, 4-Box Model + \item Archaeological Evidence --- The Record, Its Biases, What It Gives Us + \item ML on Archaeological Data --- Autoencoder on Faunal Remains + \item Approximate Bayesian Computation --- Coupling Data \& Models + \item Conclusion \pause --- Open Questions \& Connections to CCS + \end{itemize} \end{frame} -\section{The Problem: Scales and Data} +%% ═══════════════════════════════════════════════════════════════════════════ +\section{Introduction} +\sectiondivider{Introduction} -%% ── Frame 1 ────────────────────────────────────────────────────────────── -\begin{frame}{Computational Methods Have Transformed Cultural Research} - \begin{columns}[T] - \begin{column}{0.55\textwidth} - \textbf{What we can now do:} +%% ── What is Cultural Evolution? ───────────────────────────────────────── +\begin{frame}{Cultural Change} + ``Information, traditions, behaviours transmitted socially + (via direct or indirect interactions with peers)'' + + \vspace{6pt} + \begin{itemize}[<+->] + \item Languages, technologies, artistic styles, subsistence strategies\ldots + \item \textbf{Changes of frequencies} of cultural variants over time + \item Analogous to biological evolution --- but with distinct mechanisms + \end{itemize} + + \vspace{8pt} + \uncover<4->{% + \begin{center} + \begin{tikzpicture}[ + icon/.style={draw=ifsapurple, rounded corners=3pt, minimum size=1.2cm, + align=center, font=\scriptsize, fill=purplelight, line width=0.6pt} + ] + \node[icon] (a) at (0,0) {words}; + \node[icon] (b) at (2.5,0) {pottery}; + \node[icon] (c) at (5,0) {tools}; + \node[icon] (d) at (7.5,0) {food\\practices}; + \node[icon] (e) at (10,0) {digital\\culture}; + \end{tikzpicture} + \end{center} + } +\end{frame} + +%% ── Understanding Cultural Change ─────────────────────────────────────── +\begin{frame}{Understanding Cultural Change} + \uncover<+->{What drives these changes?} + + \begin{columns}[t] + \column{.50\textwidth} + \vspace{4pt} + \begin{itemize}[<+->] + \item Environmental pressures + \item Social network structure + \item Cognitive biases \& learning strategies + \item Demographic processes + \end{itemize} + + \column{.50\textwidth} + \uncover<6->{% + At relatively large geographical \emph{\&} temporal scales: + \vspace{4pt} \begin{itemize} - \item Mine large cultural datasets (texts, images, artefacts) - \item Extract meaningful patterns without prior theory - \item Apply ML, Bayesian inference, network analysis,\\dimensionality reduction + \item Limited applicability of general theories + \item Limited use of experiments + \item Limited/noisy/biased empirical evidence \end{itemize} \vspace{6pt} - \textbf{Result:} unprecedented empirical reach + \textbf{How to study meso-scale cultural evolution?} + } + \end{columns} +\end{frame} + +%% ── The COREX Project ─────────────────────────────────────────────────── +\begin{frame}{The COREX Project (ERC)} + \begin{columns}[T] + \begin{column}{0.55\textwidth} + \textbf{CO}mputational \textbf{R}esearch on Cultural \textbf{E}volution + \textbf{X}-disciplinary + + \vspace{8pt} + \begin{itemize}[<+->] + \item ERC-funded project at UCL (Dept.\ GEE) + \item Studying cultural evolution through \textbf{computational} + and \textbf{archaeological} approaches + \item Integrating agent-based models, ML, and Bayesian inference + with large archaeological databases + \item Focus on subsistence strategies, material culture, + and demographic dynamics + \end{itemize} \end{column} \begin{column}{0.42\textwidth} - \begin{block}{Key methods} + \pause + \begin{block}{Key Data Sources} \small - Machine learning\\ - Bayesian inference\\ - Network analysis\\ - Dimensionality reduction\\ - Agent-based modelling + Faunal assemblages\\ + Isotope data, ${}^{14}$C dates\\ + Ancient DNA\\ + Material culture typologies \end{block} + \vspace{6pt} + \begin{exampleblock}{Collaborations} + \small + ENCOUNTER (Cambridge)\\ + DySoC (UTK)\\ + BIAD consortium + \end{exampleblock} \end{column} \end{columns} \end{frame} -%% ── Frame 2 ────────────────────────────────────────────────────────────── -\begin{frame}{But There Are Limits} - \begin{alertblock}{The bias problem} - These methods remain biased toward \textbf{certain types of data} - and \textbf{certain scales of analysis} - \end{alertblock} - \vspace{10pt} - \begin{itemize} - \item Most work focuses on \emph{large, digitised, recent} corpora - \item Societies without extensive textual records are underrepresented - \item Local patterns ≠ global mechanisms - \end{itemize} - \vspace{10pt} - \begin{exampleblock}{The challenge} - How do we understand \textbf{general human cultural behaviour at scale},\\ - including societies that have left \textbf{few easily interpretable traces}? - \end{exampleblock} +%% ── Bridging Scales ───────────────────────────────────────────────────── +\begin{frame}{Bridging Scales} + \begin{center} + \begin{tikzpicture}[ + box/.style={draw=ifsapurple, rounded corners=5pt, minimum height=1.6cm, + text width=3cm, align=center, font=\small, line width=0.8pt}, + arr/.style={-{Stealth[length=5pt]}, thick, ifsapurple!60, line width=1pt}, + bigarr/.style={-{Stealth[length=6pt]}, very thick, accentred, line width=1.5pt} + ] + % Local + \node[box, fill=purplelight] (local) at (0,0) + {\textbf{Local}\\Individual\\interactions\\[2pt]\footnotesize ethnography}; + + % Meso + \node[box, fill=accentgold!25, draw=accentgold!80!black, line width=1.4pt] + (meso) at (5.5,0) + {\textbf{Mesoscale}\\Regional dynamics\\over millennia\\[2pt] + \footnotesize\color{accentred} our target}; + + % Global + \node[box, fill=purplelight] (global) at (11,0) + {\textbf{Global}\\Cross-cultural\\universals\\[2pt]\footnotesize big data}; + + % Arrows + \draw[arr] (local) -- (meso); + \draw[arr] (global) -- (meso); + + % Bottom label + \node[font=\footnotesize\itshape, ifsapurple] at (5.5,-1.6) + {Primary evidence: the \textbf{archaeological record}}; + \end{tikzpicture} + \end{center} + \vspace{4pt} + \pause + \begin{block}{The approach} + Model \textbf{local interactions} (ABM) $\to$ + Generate \textbf{regional patterns} $\to$ + Compare with \textbf{empirical data} $\to$ + Constrain \textbf{transmission processes} + \end{block} \end{frame} -%% ── Frame 3 ────────────────────────────────────────────────────────────── -\begin{frame}{The Mesoscale Gap} + +%% ═══════════════════════════════════════════════════════════════════════════ +\section[Models]{Computational Models} +\sectiondivider{Computational Models} + +%% ── Computational Modelling Overview ──────────────────────────────────── +\begin{frame}{Computational Modelling} + \begin{columns}[t] + \column{.60\textwidth} + \begin{itemize}[<+->] + \item Model local interactions to explore hypotheses + at different scales (\textbf{ABM}) + \item Extract empirical patterns + (Bayesian stats, ML,\ldots) + \item Test method robustness + (`tactical simulation') + \end{itemize} + \column{.40\textwidth} + \uncover<2->{% + \begin{block}{Epstein (2008)} + \small ``If you didn't grow it,\\you didn't explain it.'' + \end{block} + } + \end{columns} +\end{frame} + +%% ── Agent-Based Modelling ─────────────────────────────────────────────── +\begin{frame}{Agent-Based Modelling} + \begin{columns}[t] + \column{.55\textwidth} + \begin{itemize}[<+->] + \item Explicitly describe low-level interactions + \item Formalise, generate, and explore hypotheses + \item Reproducible and testable descriptions + \item Flexible: demography, spatial structure, + multiple transmission pathways + \end{itemize} + + \column{.45\textwidth} + \uncover<2->{% + \begin{center} + \begin{tikzpicture}[scale=0.7, + agent/.style={circle, draw=ifsapurple, fill=purplelight, + minimum size=5mm, inner sep=0pt, font=\tiny\bfseries}, + link/.style={ifsapurple!40, line width=0.6pt} + ] + % Grid of agents + \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, + 3.5/1.5/f,0/3/g,1.5/2.8/h,3/3.2/i} { + \node[agent] (\lab) at (\x,\y) {}; + } + % Links + \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} { + \draw[link] (\a) -- (\b); + } + % Highlight a transmission event + \draw[-{Stealth[length=4pt]}, accentred, thick] (e) -- (h) + node[midway, right, font=\tiny] {copy}; + % Label + \node[font=\scriptsize, ifsapurple, below] at (1.5,-0.5) + {agents on a network}; + \end{tikzpicture} + \end{center} + } + \end{columns} +\end{frame} + +%% ── The 4-Box Model ──────────────────────────────────────────────────── +\begin{frame}{Cultural Transmission --- The 4-Box Model} + \begin{columns}[t] + \column{.45\textwidth} + \textbf{Vidiella et al.\ (2022):} + \begin{align*} + \Pr(i,t{+}1) = \frac{1}{Y_t}\, p_i(t)^{\alert{J}}\, e^{\alert{\beta}\, U_i + \psi} + \end{align*} + \begin{itemize}[<+->] + \item $\alert{J}$: social conformity (frequency dependence) + \item $\alert{\beta}$: transparency of intrinsic utility + \end{itemize} + \uncover<3->{A 2D space to classify cultural change:} + + \column{.55\textwidth} + \uncover<3->{% + \begin{center} + \begin{tikzpicture}[scale=0.85, + box/.style={draw=ifsapurple, rounded corners=3pt, + minimum height=1.4cm, text width=2.6cm, align=center, + font=\scriptsize, line width=0.6pt} + ] + % Axes + \draw[-{Stealth[length=5pt]}, thick, ifsapurple] + (-0.2,0) -- (6.2,0) node[right, font=\small] {$J$ (conformity)}; + \draw[-{Stealth[length=5pt]}, thick, ifsapurple] + (0,-0.2) -- (0,4.8) node[above, font=\small] {$\beta$ (utility)}; + + % Quadrants + \node[box, fill=purplelight] at (1.5,1.2) {Drift\\(neutral)}; + \node[box, fill=accentgold!20] at (4.5,1.2) {Conformity\\bias}; + \node[box, fill=ifsapurple!12] at (1.5,3.5) {Content\\bias}; + \node[box, fill=accentred!12] at (4.5,3.5) {Guided\\variation}; + + % Parameter labels + \node[font=\tiny, midgray] at (1.5,-0.5) {low $J$}; + \node[font=\tiny, midgray] at (4.5,-0.5) {high $J$}; + \node[font=\tiny, midgray, rotate=90] at (-0.6,1.2) {low $\beta$}; + \node[font=\tiny, midgray, rotate=90] at (-0.6,3.5) {high $\beta$}; + \end{tikzpicture} + \end{center} + } + \end{columns} +\end{frame} + +%% ── Cultural Transmission Pathways ────────────────────────────────────── +\begin{frame}{Cultural Transmission Pathways} \begin{center} - \begin{tikzpicture} - \draw[->, thick, pslblue] (0,0) -- (10,0) node[right] {\textbf{Scale}}; - % Local - \node[draw, rounded corners, fill=psllight, text width=2cm, align=center] - at (1.5,1.2) {\small Local\\interactions}; - % Meso - \node[draw, rounded corners, fill=pslgold!30, text width=2.5cm, align=center, - thick, pslgold] - at (5,1.8) {\textbf{Mesoscale}\\Regional\\Millennial}; - \node[below=2pt] at (5,0.8) {\footnotesize \textit{our target}}; - % Global - \node[draw, rounded corners, fill=psllight, text width=2.2cm, align=center] - at (8.5,1.2) {\small Global\\patterns}; - % Arrows - \draw[->, midgray] (2.5,1.2) -- (3.8,1.5); - \draw[->, midgray] (7.2,1.2) -- (6.2,1.5); + \begin{tikzpicture}[ + gen/.style={draw=ifsapurple, rounded corners=2pt, minimum height=0.8cm, + text width=2.2cm, align=center, font=\scriptsize, fill=purplelight}, + arr/.style={-{Stealth[length=4pt]}, ifsapurple, line width=0.7pt}, + lab/.style={font=\tiny, midgray, align=center} + ] + % Parent generation + \node[gen, fill=ifsapurple!20] (p1) at (0,3) {Parent A}; + \node[gen, fill=ifsapurple!20] (p2) at (3,3) {Parent B}; + \node[gen, fill=ifsapurple!12] (elder) at (6,3) {Elder / Peer}; + \node[gen, fill=accentgold!15] (comm) at (9.5,3) {Community}; + + % 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 Processes unfolding at \textbf{regional level over millennia} - \item Mechanisms observed locally must be \textbf{extrapolated} carefully - \item Evidence is often \textbf{archaeological} — fragmented, biased, indirect + \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} -\section{The Approach} +%% ── 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} -%% ── Frame 4 ────────────────────────────────────────────────────────────── -\begin{frame}{Our Proposal: Coupling Data and Models} + +%% ═══════════════════════════════════════════════════════════════════════════ +\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}[node distance=3.5cm] - \node[draw, rounded corners, fill=pslblue!15, text width=3.2cm, align=center, - minimum height=1.5cm] (data) - {\textbf{Archaeological\\Data}\\[4pt]\small ML · Bayesian\\pattern extraction}; - \node[draw, rounded corners, fill=pslgold!25, text width=3.2cm, align=center, - minimum height=1.5cm, right of=data] (model) - {\textbf{Agent-Based\\Models}\\[4pt]\small Cultural change\\exploration}; - \node[draw, rounded corners, fill=accent!15, text width=3cm, align=center, - minimum height=1.5cm, right of=model] (hypo) - {\textbf{Hypothesis\\Testing}\\[4pt]\small Mesoscale\\predictions}; - \draw[->, thick, pslblue, line width=1.5pt] (data) -- (model); - \draw[->, thick, pslblue, line width=1.5pt] (model) -- (hypo); - \draw[->, thick, midgray, dashed] (hypo.south) .. controls +(0,-1.2) and +(0,-1.2) .. - (data.south) node[midway, below] {\small feedback}; + \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} -%% ── Frame 5 ────────────────────────────────────────────────────────────── -\begin{frame}{Why Agent-Based Modelling?} +%% ── ABC in Practice ───────────────────────────────────────────────────── +\begin{frame}{ABC in Practice --- Summary Statistics Matter} \begin{columns}[T] - \begin{column}{0.5\textwidth} - \textbf{ABM allows us to:} - \begin{itemize} - \item Model \textbf{individual decisions} and local interactions - \item Observe \textbf{emergent} population-level patterns - \item Test hypotheses where \textbf{controlled experiments} are impossible - \item Explore \textbf{counterfactuals} and sensitivity - \end{itemize} + \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} - \begin{block}{Epstein (2008)} - \small ``The agent-based computational model is a new tool for social science\ldots it generates candidate explanations.'' - \end{block} - \vspace{6pt} - \begin{block}{Levins (1966)} - \small Models trade off generality, realism, and precision. Choose deliberately. - \end{block} + \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} -\section{Case Studies} +%% ── 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}; -%% ── Frame 6 ────────────────────────────────────────────────────────────── -\begin{frame}{Case Study 1: Cultural Diversity and Taphonomic Bias} - \begin{itemize} - \item \textbf{Question:} How does archaeological preservation bias our view\\of past cultural diversity? - \item \textbf{Approach:} Network-based community detection + ABM - \item \textbf{Data:} Bronze Age assemblages (BIAD / EPNet datasets) - \item \textbf{Method:} Simulate cultural exchange networks,\\apply taphonomic loss, compare to empirical patterns - \end{itemize} - \vspace{8pt} - \begin{exampleblock}{Key finding} - Spatial structure and mobility rates interact to determine\\ - how much diversity is \emph{observable} vs. \emph{lost to the record} - \end{exampleblock} + % 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} -%% ── Frame 7 ────────────────────────────────────────────────────────────── -\begin{frame}{Case Study 2: Patterns at Regional Scale} - \begin{itemize} - \item \textbf{Question:} Can we extract meaningful cultural signals\\from heterogeneous archaeological datasets? - \item \textbf{Approach:} Machine learning + Bayesian classification\\of artefact assemblages - \item \textbf{Tools:} Dimensionality reduction (PCA, UMAP),\\Bayesian mixture models - \item \textbf{Coupling:} Patterns inform ABM parameter spaces\\for cultural transmission models - \end{itemize} - \vspace{8pt} - \begin{alertblock}{The challenge of the record} - Archaeological evidence is fragmentary, spatially biased,\\ - and temporally coarse — methods must account for this explicitly - \end{alertblock} -\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}; -%% ── Frame 8 ────────────────────────────────────────────────────────────── -\begin{frame}{Case Study 3: Modelling Cultural Change Trajectories} - \begin{itemize} - \item \textbf{Question:} What cultural transmission processes\\generate the patterns we observe? - \item \textbf{ABM setup:} Agents represent social groups;\\traits spread via biased transmission, drift, migration - \item \textbf{Validation:} Simulated distributions compared to archaeological record - \item \textbf{Scale:} Regional networks over centuries to millennia - \end{itemize} - \vspace{8pt} - \begin{block}{Why this matters for C2S} - The same pipeline applies to \textbf{textual/cultural corpora}:\\ - extract patterns → model mechanisms → test hypotheses + % 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{Perspectives} -%% ── Frame 9 ────────────────────────────────────────────────────────────── -\begin{frame}{Connecting to Computational Cultural Science} +%% ═══════════════════════════════════════════════════════════════════════════ +\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} - \textbf{From archaeology to culture broadly:} - \begin{itemize} - \item Same questions, different data types - \item Texts, images, media as ``cultural assemblages'' - \item Disruption metrics (Kim et al. 2026)\\as cultural fitness proxies - \item NLP + ABM for media dynamics - \end{itemize} + \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} - \textbf{Open challenges:} - \begin{itemize} - \item Model validation without ground truth - \item Integrating heterogeneous data types - \item Interpretability of ML-extracted patterns - \item Theory–data feedback loops - \end{itemize} + \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} -%% ── Frame 10 ───────────────────────────────────────────────────────────── -\begin{frame}{Summary} - \begin{enumerate} - \item Computational methods have \textbf{transformed} cultural research\\ - but remain biased toward certain data and scales - \vspace{6pt} - \item The \textbf{mesoscale} — regional processes over millennia —\\ - is tractable by coupling ML/Bayesian extraction with ABM - \vspace{6pt} - \item \textbf{Archaeological evidence} is a hard test case:\\ - methods that work here generalise - \vspace{6pt} - \item This pipeline connects directly to broader \textbf{computational\\ - cultural science}: patterns → mechanisms → predictions - \end{enumerate} +%% ── 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 ───────────────────────────────────────────────────────────── -\begin{frame}[standout] +%% ── Thank You ─────────────────────────────────────────────────────────── +\begingroup +\setbeamertemplate{footline}{} +\setbeamercolor{background canvas}{bg=ifsapurple,fg=white} +\frame[plain,noframenumbering]{% \centering - \Large Thank you\\[12pt] - \normalsize - \href{mailto:s.carrignon@ucl.ac.uk}{s.carrignon@ucl.ac.uk}\\[6pt] - UCL GEE · CDAL · ENCOUNTER · UGI\\[10pt] - \small - Slides \& code: \href{https://github.com/simoncarrignon}{github.com/simoncarrignon}\\[16pt] - \textit{Computational Cultural Science Workshop}\\ - École nationale des Chartes -- PSL · Paris · May 2026 -\end{frame} + \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 -%% ── Backup slides ───────────────────────────────────────────────────────── +%% ═══════════════════════════════════════════════════════════════════════════ \appendix +%% ── Backup: References ────────────────────────────────────────────────── \begin{frame}{References} \small \begin{itemize} - \item Epstein, J.M. (2008). Why Model? \textit{JASSS} 11(4):12. - \item Levins, R. (1966). The strategy of model building in population biology. - \textit{Am. Sci.} 54:421--431. - \item Bonabeau, E. (2002). Agent-based modeling. \textit{PNAS} 99:7280--7287. - \item Reichenbach et al. (2007). Mobility promotes and jeopardizes biodiversity. - \textit{Nature} 448:1046--1049. - \item Kim, Kojaku \& Ahn (2026). Uncovering simultaneous breakthroughs. - \textit{Science Advances} 12(14). + \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} -\begin{frame}{The Archaeological Record: Key Challenges} - \begin{itemize} - \item \textbf{Preservation bias:} organic materials lost; hard materials persist - \item \textbf{Spatial bias:} sampling effort uneven across regions - \item \textbf{Temporal resolution:} centuries collapsed into single ``phases'' - \item \textbf{Inference gap:} behaviour → material culture → preservation → observation - \end{itemize} - \vspace{6pt} - Methods must be \textbf{explicitly designed} to account for these filters,\\ - not applied naively from other domains. -\end{frame} - \end{document}