adding more applets, game of life, etc

berlinbrown · Dec 29, 2011 · 5d7b86c · 5d7b86c
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diff --git a/applets/scala/GameOfLifeCellular/.classpath b/applets/scala/GameOfLifeCellular/.classpath
@@ -0,0 +1,11 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<classpath>
+	<classpathentry kind="src" path="src/main/java"/>
+	<classpathentry kind="src" path="src/main/scala"/>
+	<classpathentry kind="con" path="org.scala-ide.sdt.launching.SCALA_CONTAINER"/>
+	<classpathentry kind="con" path="org.eclipse.jdt.launching.JRE_CONTAINER"/>
+	<classpathentry kind="lib" path="lib/unmanaged/log4j-1.2.16.jar"/>
+	<classpathentry kind="lib" path="lib/unmanaged/slf4j-log4j12-1.6.1.jar"/>
+	<classpathentry kind="lib" path="lib/unmanaged/slf4j-api-1.6.1.jar"/>
+	<classpathentry kind="output" path="src/main/webapp/WEB-INF/classes"/>
+</classpath>
diff --git a/applets/scala/GameOfLifeCellular/.project b/applets/scala/GameOfLifeCellular/.project
@@ -0,0 +1,30 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<projectDescription>
+	<name>GameOfLife</name>
+	<comment></comment>
+	<projects>
+	</projects>
+	<buildSpec>
+		<buildCommand>
+			<name>net.sourceforge.texlipse.builder.TexlipseBuilder</name>
+			<arguments>
+			</arguments>
+		</buildCommand>
+		<buildCommand>
+			<name>org.scala-ide.sdt.core.scalabuilder</name>
+			<arguments>
+			</arguments>
+		</buildCommand>
+		<buildCommand>
+			<name>ch.epfl.lamp.sdt.core.scalabuilder</name>
+			<arguments>
+			</arguments>
+		</buildCommand>
+	</buildSpec>
+	<natures>
+		<nature>net.sourceforge.texlipse.builder.TexlipseNature</nature>
+		<nature>ch.epfl.lamp.sdt.core.scalanature</nature>
+		<nature>org.scala-ide.sdt.core.scalanature</nature>
+		<nature>org.eclipse.jdt.core.javanature</nature>
+	</natures>
+</projectDescription>
diff --git a/applets/scala/GameOfLifeCellular/.scala_dependencies b/applets/scala/GameOfLifeCellular/.scala_dependencies
diff --git a/applets/scala/GameOfLifeCellular/README.txt b/applets/scala/GameOfLifeCellular/README.txt
@@ -0,0 +1,118 @@
+###########################################################
+# README
+# Created: 1/11/2011
+###########################################################
+
+    About: BottomUpCellLifeGame
+    -----------------------------
+
+    Also see:
+
+    http://doingitwrongnotebook.googlecode.com/svn/trunk/doingitwrong_phase2/scala2/GameOfLife/src/main/scala/
+    http://code.google.com/p/ainotebook/wiki/BottomUpArtificialLifeSimulation
+
+    -----
+    Notes:
+    -----
+
+    - The system is slightly interesting.  You can monitor the balance with the number of live cells. 
+      You may notice a shift in mutations as cells grow away from the center.
+
+    -  With only a few mutations, the color of cells tend to shift in color over time.
+
+    - It takes many iterations for emergent behavior to emerge.
+
+    - Code wise not really that interesting but already we can visualize the emergent behavior.
+
+    - Cheating to make the simulation feasible 
+
+    -----
+    Building:
+    -----
+    Artificial Life Demo - launch the sbt.bat script and type compile at the prompt
+    - sbt - at prompt compile
+    - sbt - at prompt package
+    - sbt - at prompt package-src 
+
+
+    -----
+    Now Using:
+    -----  
+    Scala Version: Scala 2.9.0 r24613 b20110328152330
+
+    Previously Using scala: 2.8.0.r22118-b20106020
+
+
+    sbt - simple build tool
+    -----    
+
+    Simple game of life in Scala and using scala.swing api.
+    Doing it wrong version, no refactoring.
+
+    Keywords: rule30, rule190, squaringrule, wolfram
+
+    -----
+    Running:
+    -----
+    Run the applet[1-4].html files in a modern browser.  The java applets will execute. 
+
+    -----
+    Adding svn propset on html files.
+    svn propset svn:mime-type 'text/html' applet.html 
+    -----
+
+    Berlin Brown - berlin dot brown _at_ gmail dot com
+    keywords: cells, dna, replication, gameoflife, scala, java, alife, artificiallife
+
+---------------------------------------
+
+The field of artificial intelligence in computer science focuses on many
+different areas of computing from computer vision to natural language
+processing. These top-down approaches typically concentrate on human behavior
+or other animal functions. In this article we look at a bottom-up approach to
+artificial life and how emergent cell behavior can produce interesting results.
+With this bottom-up alife approach, we are not interested in solving any
+particular task, but we are interested in observing the adaptive nature of the
+entities in our simulation. We also wanted to introduce those more familiar with
+software engineering to biological systems and evolutionary theory concepts.
+
+Life is all around us. Even with inorganic material it is possible that
+microscopic organisms are covering that surface. Moving forward if we want to
+study, analyze and work with artificial agents, we might consider systems that
+have evolved behavior over a series of steps. We should not necessarily build a
+specific tool with a specific purpose but the creature that is built from the
+system may produce interesting properties which are unlike the clean-room
+created software that we create today. Most software and hardware today is
+written to specification, line for line, most code written for today's systems
+are created by man. That software is designed, coded and tested. It would be
+interesting if we could start a biological like system and interesting behavior
+from the system evolves over time.
+
+Conway's Game of Life cellular automaton is one of the most prominent examples
+of cellular automata theory. The one dimensional program consists of a cell grid
+typically with several dozen or more rows and similar number of columns. Each
+cell on the grid has an on or off Boolean state. Every cell on the grid survives
+or dies to the next generation depending on the game of life rules. If there are
+too many neighbors surrounding a cell then the cell dies due to overcrowding. If
+there is only one neighbor cell, the base cell dies due to under-population.
+Activity on a particular cell is not interesting but when you run the entire
+system for many generations, a group of patterns begin to form.
+
+You may notice some common patterns in the figure. After so many iterations
+through the game of life rules, only a few cells tend to stay alive. We started
+with a large random number of alive cells and over time those cells died off. In
+a controlled environment you may begin with carefully placed live cells and
+monitor the patterns that emerge to model some other natural phenomena.
+
+Summary
+
+Moving forward if we want to study, analyze and work with artificial agents, we
+might consider systems that have evolved behavior over a series of steps. We
+might not build a specific tool with a specific purpose but the creature that is
+built from the system may produce interesting properties which are unlike the
+clean-room created software that we create today.
+
+With this artificial life approach, but we also want to study the simple life
+forms first before moving too fast forward like human behavior.
+
+-- Berlin Brown
diff --git a/applets/scala/GameOfLifeCellular/TODO b/applets/scala/GameOfLifeCellular/TODO
@@ -0,0 +1,8 @@
+###########################################################
+# TODO
+###########################################################
+
+For bottom up alife sim:
+
+- Add simple charts
+
diff --git a/applets/scala/GameOfLifeCellular/_applet3.html b/applets/scala/GameOfLifeCellular/_applet3.html
@@ -0,0 +1,21 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html>
+  <head>
+    <title>Applet Page</title>
+    <meta http-equiv="Content-Type" content="text/html; charset=windows-1252">
+    <script src="deployJava.js"></script>
+  </head>
+  <body>
+    <h3>Cellular Automata Game of Life Applet</h3>    
+
+    <script>
+        var attributes = {
+        	    code:    'org.berlin.gol.sound.GameOfLifeSoundApplet',
+        	    archive: 'scala-library.jar,scala-swing.jar,gameoflifesound.jar',
+        	    width:400, height:400
+        	    };
+        var parameters = {  };
+        deployJava.runApplet(attributes, parameters, '1.6');
+    </script>
+  </body>
+</html>
diff --git a/applets/scala/GameOfLifeCellular/alife.bat b/applets/scala/GameOfLifeCellular/alife.bat
@@ -0,0 +1,2 @@
+set SCRIPT_DIR=%~dp0
+java -Xmx300M -classpath "%SCRIPT_DIR%;slf4j-api-1.6.1.jar;%SCRIPT_DIR%slf4j-log4j12-1.6.1.jar;%SCRIPT_DIR%log4j-1.2.16.jar;%SCRIPT_DIR%scala-swing.jar;%SCRIPT_DIR%scala-library.jar;%SCRIPT_DIR%alife_2.8.0-1.0.jar" org.berlin2.bottomuplife.CellSimulation
diff --git a/applets/scala/GameOfLifeCellular/applet.html b/applets/scala/GameOfLifeCellular/applet.html
@@ -0,0 +1,53 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html>
+  <head>
+    <title>Applet Page</title>
+    <meta http-equiv="Content-Type" content="text/html; charset=windows-1252">
+    <script src="deployJava.js"></script>
+  </head>
+  <body>
+    <h1>Game of Life Applet</h1>
+
+     <p>
+    Conway's Game of Life cellular automaton is one of the most prominent examples of cellular automata theory. 
+    The one dimensional program consists of a cell grid typically with several dozen or more rows and similar 
+    number of columns. Each cell on the grid has an on or off Boolean state. Every cell on the grid survives or dies 
+    to the next generation depending on the game of life rules. If there are too many neighbors surrounding a 
+    cell then the cell dies due to overcrowding. If there is only one neighbor cell, 
+    the base cell dies due to under-population. Activity on a particular cell is not interesting 
+    but when you run the entire system for many generations, a group of patterns begin to form.
+
+    <br /> <br />
+
+    Stephan Wolfram is the founder of Wolfram|Research, his company is known for the popular Mathematica software suite 
+    and Wolfram|Alpha knowledge engine. He did not initially discover cellular automata but recently 
+    he has been a prominent figure in its advocacy. He spent 10 years working on his book, A New Kind of Science. 
+    In the 1300 page tome, he discusses how cellular automata can be applied to every field of science from biology to physics. 
+    NKA is a detailed study of cellular automata programs.
+
+    <br /> <br />
+
+    Cellular automata is often used with data compression, cryptography, artificial intelligence, urban planning, 
+    financial market modeling, music generation, and 3D terrain generation. If you are a software engineer, 
+    you may have to step back and consider how cellular automata patterns emerge and understand the nature of 
+    the dynamic system before looking for a typical software library. CA is not normally seen in everyday applications. 
+    Consider this when you look at some random pattern, don't think of the phenomenon as a random sequence of events that 
+    cannot be replicated, think of the event in terms of a cellular automaton. Try to imagine the rules that could 
+    model that natural behavior. Modeling seemingly random patterns is an area where cellular automata is being widely used. Urban planning departments are integrating geographic information systems (GIS) 
+    with cellular automata in an attempt to predict growth in an area of a city.    
+    </p>
+
+    Example automata applet in Scala: -- Berlin Brown
+    <br />
+
+    <script>
+        var attributes = {
+        	    code:    'org.berlin.gol.GameOfLifeApplet',
+        	    archive: 'gameoflife.jar',
+        	    width:600, height:600
+        	    };
+        var parameters = {  };
+        deployJava.runApplet(attributes, parameters, '1.6');
+    </script>
+  </body>
+</html>
diff --git a/applets/scala/GameOfLifeCellular/applet2.html b/applets/scala/GameOfLifeCellular/applet2.html
@@ -0,0 +1,52 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html>
+  <head>
+    <title>Applet Page</title>
+    <meta http-equiv="Content-Type" content="text/html; charset=windows-1252">
+    <script src="deployJava.js"></script>
+  </head>
+  <body>    
+    <h3>Basic Wolfram Cellular Automata Applet</h3>
+
+    <p>
+    Conway's Game of Life cellular automaton is one of the most prominent examples of cellular automata theory. 
+    The one dimensional program consists of a cell grid typically with several dozen or more rows and similar 
+    number of columns. Each cell on the grid has an on or off Boolean state. Every cell on the grid survives or dies 
+    to the next generation depending on the game of life rules. If there are too many neighbors surrounding a 
+    cell then the cell dies due to overcrowding. If there is only one neighbor cell, 
+    the base cell dies due to under-population. Activity on a particular cell is not interesting 
+    but when you run the entire system for many generations, a group of patterns begin to form.
+
+    <br /> <br />
+
+    Stephan Wolfram is the founder of Wolfram|Research, his company is known for the popular Mathematica software suite 
+    and Wolfram|Alpha knowledge engine. He did not initially discover cellular automata but recently 
+    he has been a prominent figure in its advocacy. He spent 10 years working on his book, A New Kind of Science. 
+    In the 1300 page tome, he discusses how cellular automata can be applied to every field of science from biology to physics. 
+    NKA is a detailed study of cellular automata programs.
+
+    <br /> <br />
+
+    Cellular automata is often used with data compression, cryptography, artificial intelligence, urban planning, 
+    financial market modeling, music generation, and 3D terrain generation. If you are a software engineer, 
+    you may have to step back and consider how cellular automata patterns emerge and understand the nature of 
+    the dynamic system before looking for a typical software library. CA is not normally seen in everyday applications. 
+    Consider this when you look at some random pattern, don't think of the phenomenon as a random sequence of events that 
+    cannot be replicated, think of the event in terms of a cellular automaton. Try to imagine the rules that could 
+    model that natural behavior. Modeling seemingly random patterns is an area where cellular automata is being widely used. Urban planning departments are integrating geographic information systems (GIS) 
+    with cellular automata in an attempt to predict growth in an area of a city.    
+    </p>
+
+    Example automata applet in Scala: -- Berlin Brown
+    <br />
+    <script>
+        var attributes = {
+        	    code:    'org.berlin.automata.AutomataApplet',
+        	    archive: 'scala-library.jar,scala-swing.jar,automatascala.jar',
+        	    width:1000, height:1000
+        	    };
+        var parameters = {  };
+        deployJava.runApplet(attributes, parameters, '1.6');
+    </script>
+  </body>
+</html>
diff --git a/applets/scala/GameOfLifeCellular/applet4.html b/applets/scala/GameOfLifeCellular/applet4.html
@@ -0,0 +1,52 @@
+<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
+<html>
+  <head>
+    <title>Applet Page</title>
+    <meta http-equiv="Content-Type" content="text/html; charset=windows-1252">
+    <script src="deployJava.js"></script>
+  </head>
+  <body>
+    <h3>Cellular Squaring Automata Applet</h3>
+
+       <p>
+    Conway's Game of Life cellular automaton is one of the most prominent examples of cellular automata theory. 
+    The one dimensional program consists of a cell grid typically with several dozen or more rows and similar 
+    number of columns. Each cell on the grid has an on or off Boolean state. Every cell on the grid survives or dies 
+    to the next generation depending on the game of life rules. If there are too many neighbors surrounding a 
+    cell then the cell dies due to overcrowding. If there is only one neighbor cell, 
+    the base cell dies due to under-population. Activity on a particular cell is not interesting 
+    but when you run the entire system for many generations, a group of patterns begin to form.
+
+    <br /> <br />
+
+    Stephan Wolfram is the founder of Wolfram|Research, his company is known for the popular Mathematica software suite 
+    and Wolfram|Alpha knowledge engine. He did not initially discover cellular automata but recently 
+    he has been a prominent figure in its advocacy. He spent 10 years working on his book, A New Kind of Science. 
+    In the 1300 page tome, he discusses how cellular automata can be applied to every field of science from biology to physics. 
+    NKA is a detailed study of cellular automata programs.
+
+    <br /> <br />
+
+    Cellular automata is often used with data compression, cryptography, artificial intelligence, urban planning, 
+    financial market modeling, music generation, and 3D terrain generation. If you are a software engineer, 
+    you may have to step back and consider how cellular automata patterns emerge and understand the nature of 
+    the dynamic system before looking for a typical software library. CA is not normally seen in everyday applications. 
+    Consider this when you look at some random pattern, don't think of the phenomenon as a random sequence of events that 
+    cannot be replicated, think of the event in terms of a cellular automaton. Try to imagine the rules that could 
+    model that natural behavior. Modeling seemingly random patterns is an area where cellular automata is being widely used. Urban planning departments are integrating geographic information systems (GIS) 
+    with cellular automata in an attempt to predict growth in an area of a city.    
+    </p>
+
+    Example automata applet in Scala: -- Berlin Brown
+    <br />
+    <script>
+        var attributes = {
+        	    code:    'org.berlin.automata.squaring.CellularAutomataSquareApplet',
+        	    archive: 'scala-library.jar,scala-swing.jar,squaringautomata.jar',
+        	    width:700, height:700
+        	    };
+        var parameters = {  };
+        deployJava.runApplet(attributes, parameters, '1.6');
+    </script>
+  </body>
+</html>
diff --git a/applets/scala/GameOfLifeCellular/applet_gadget.xml b/applets/scala/GameOfLifeCellular/applet_gadget.xml
@@ -0,0 +1,5 @@
+<?xml version="1.0" encoding="UTF-8" ?> 
+<Module>
+  <ModulePrefs title="remote content example" />
+  <Content type="url" href="http://doingitwrongnotebook.googlecode.com/svn/trunk/doingitwrong_phase2/scala2/GameOfLife/applet.html" />
+</Module>
diff --git a/applets/scala/GameOfLifeCellular/applet_gadget2.xml b/applets/scala/GameOfLifeCellular/applet_gadget2.xml
@@ -0,0 +1,5 @@
+<?xml version="1.0" encoding="UTF-8" ?> 
+<Module>
+  <ModulePrefs title="remote content example" />
+  <Content type="url" href="http://doingitwrongnotebook.googlecode.com/svn/trunk/doingitwrong_phase2/scala2/GameOfLife/applet2.html" />
+</Module>
diff --git a/applets/scala/GameOfLifeCellular/applet_gadget3.xml b/applets/scala/GameOfLifeCellular/applet_gadget3.xml
@@ -0,0 +1,5 @@
+<?xml version="1.0" encoding="UTF-8" ?> 
+<Module>
+  <ModulePrefs title="remote content example" />
+  <Content type="url" href="http://doingitwrongnotebook.googlecode.com/svn/trunk/doingitwrong_phase2/scala2/GameOfLife/applet3.html" />
+</Module>
diff --git a/applets/scala/GameOfLifeCellular/applet_gadget4.xml b/applets/scala/GameOfLifeCellular/applet_gadget4.xml
@@ -0,0 +1,5 @@
+<?xml version="1.0" encoding="UTF-8" ?> 
+<Module>
+  <ModulePrefs title="remote content example" />
+  <Content type="url" href="http://doingitwrongnotebook.googlecode.com/svn/trunk/doingitwrong_phase2/scala2/GameOfLife/applet4.html" />
+</Module>
diff --git a/applets/scala/GameOfLifeCellular/automatascala.jar b/applets/scala/GameOfLifeCellular/automatascala.jar
diff --git a/applets/scala/GameOfLifeCellular/branch.sh b/applets/scala/GameOfLifeCellular/branch.sh
@@ -0,0 +1,7 @@
+#!/bin/sh
+
+svn copy \
+  https://doingitwrongnotebook.googlecode.com/svn/trunk/doingitwrong_phase2/scala2/GameOfLife  \
+  https://doingitwrongnotebook.googlecode.com/svn/branches/ainotebookBottomUpInitRelease/doingitwrong_phase2/scala2/GameOfLife \
+ -m 'creating branch'
+