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hexboard-games
Module Materials
Commits
b873e6e9
There was a problem fetching the pipeline mini graph.
Commit
b873e6e9
authored
6 years ago
by
Joseph Walton-Rivers
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update homepage and slides for this morning
parent
1411f4f7
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_data/index.json
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_data/index.json
slides/content/metrics.tex
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slides/content/metrics.tex
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_data/index.json
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b873e6e9
...
...
@@ -77,6 +77,8 @@
"name"
:
"2"
,
"topic"
:
"AI Experiments and candidate games"
,
"links"
:
{
"metrics"
:
"code/AppMetrics.java"
,
"intro"
:
"slides_pdf/ce810-metrics.pres.pdf"
}
},
{
...
...
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slides/content/metrics.tex
+
48
−
6
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b873e6e9
...
...
@@ -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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