From b873e6e9bf23fb1f2bd9465775d7e5825fe2e271 Mon Sep 17 00:00:00 2001
From: Joseph Walton-Rivers <jwalto@essex.ac.uk>
Date: Tue, 22 May 2018 08:40:51 +0100
Subject: [PATCH] update homepage and slides for this morning
---
_data/index.json | 2 ++
slides/content/metrics.tex | 54 +++++++++++++++++++++++++++++++++-----
2 files changed, 50 insertions(+), 6 deletions(-)
diff --git a/_data/index.json b/_data/index.json
index dbebfbe..b343915 100644
--- a/_data/index.json
+++ b/_data/index.json
@@ -77,6 +77,8 @@
"name": "2",
"topic": "AI Experiments and candidate games",
"links": {
+ "metrics": "code/AppMetrics.java",
+ "intro":"slides_pdf/ce810-metrics.pres.pdf"
}
},
{
diff --git a/slides/content/metrics.tex b/slides/content/metrics.tex
index 3515d7c..0350ca7 100644
--- a/slides/content/metrics.tex
+++ b/slides/content/metrics.tex
@@ -54,7 +54,7 @@
\begin{itemize}[<+->]
\item We did these yesterday.
\item We should load the AIFactory
- \item Then use the factory in the evaluate
+ \item Then use the factory to build agents in the evaluate
\item ai.buildAI("ProRuleRushRangedBlue", settings),
\end{itemize}
\end{frame}
@@ -83,7 +83,7 @@ public Double evaluate(GameSettings settings) {
\end{minted}
\end{frame}
-\begin{frame}[fragile]{Basic}
+\begin{frame}[fragile]{Less Basic}
\begin{minted}[breaklines,tabsize=2,fontsize=\footnotesize]{Java}
public Double evaluate(GameSettings settings) {
GameState start = map.buildState(settings);
@@ -101,10 +101,6 @@ public Double evaluate(GameSettings settings) {
winCounts[winner]++;
}
}
-
- double score = winCounts[1] - winCounts[0];
- fitnessScores.put(settings, score);
- return score;
}
\end{minted}
\end{frame}
@@ -126,5 +122,51 @@ public Double evaluate(GameSettings settings) {
\end{figure}
\end{frame}
+\begin{frame}{Results}
+ \begin{table}
+ \begin{tabular}{l|l|l}
+ defRanged&atkRanged&fitness\\\hline
+ 1 & 5 & 30\\
+ 10 & 6 & 20\\
+ 4 & 2 & 20\\
+ 10 & 2 & 20
+ \end{tabular}
+
+ \pause So not a very good fitness function then...
+ \end{table}
+\end{frame}
+
+\section{User Testing}
+
+\begin{frame}{A|B Testing}
+ \begin{itemize}[<+->]
+ \item Put two versions of the game in front of someone
+ \item Ask them what one they enjoyed most
+ \item Ideally should use a large sample size (or stats)
+ \item But this isn't meant to be rigorous
+ \end{itemize}
+\end{frame}
+
+\begin{frame}{Qualitative Data}
+ \begin{itemize}[<+->]
+ \item In inform out conclusions we could ask other things
+ \begin{itemize}
+ \item Basic demographic data,
+ \item Experience with games,
+ \item Open ended questions,
+ \item Game Metrics...
+ \end{itemize}
+ \end{itemize}
+\end{frame}
+
+\section{Advice}
+
+\begin{frame}{AI experiments}
+ \begin{itemize}[<+->]
+ \item Fast iterations - don't spend too long waiting for stuff
+ \item Drop turn limits, repeats, generation counts...
+ \item See what kind of data you're getting and adapt your fitness.
+ \end{itemize}
+\end{frame}
\end{document}
--
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