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SRI International's AIC PRAiSE (Probabilistic Reasoning As Symbolic Evaluation) Library (for Java 1.8+)
/*
* Copyright (c) 2015, SRI International
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* Licensed under the The BSD 3-Clause License;
* you may not use this file except in compliance with the License.
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package com.sri.ai.praise.evaluate.run.cli;
import static com.sri.ai.util.Util.list;
import static com.sri.ai.util.Util.mapIntoList;
import java.io.IOException;
import com.sri.ai.praise.lang.ModelLanguage;
import com.sri.ai.praise.model.common.io.ModelPage;
import com.sri.ai.praise.model.common.io.PagedModelContainer;
import com.sri.ai.util.collect.IntegerIterator;
/**
* Command line interface for evaluating an election model as submitted to IJCAI 2016.
*
* @author braz
*
*/
public class EvaluationOnElectionModelCLI extends AbstractEvaluateCLI {
protected PagedModelContainer makeModelsContainer(EvaluationArgs evaluationArgs) throws IOException {
return
new PagedModelContainer(
"election",
mapIntoList(new IntegerIterator(1, 4), (Integer i) ->
new ModelPage(
ModelLanguage.HOGMv1,
"election (multiplier " + i + ")",
modelStringForDomainSize(500, i),
list("likeIncumbent > likeChallenger"))));
}
/**
* @return
*/
private String modelStringForDomainSize(int domainSize, int multiplier) {
domainSize *= multiplier;
return "random terrorAttacks : 0..20;\r\n" +
"random newJobs : 0..100; // 100K\r\n" +
"random dow: 110..180;\r\n" +
"random economyIsPoor : Boolean;\r\n" +
"random economyIsGreat : Boolean;\r\n" +
"random attackPerception: Boolean;\r\n" +
"random likeIncumbent : 0.." + domainSize + "; // 100M\r\n" +
"random likeChallenger : 0.." + domainSize + "; // 100M\r\n" +
"\r\n" +
"// P(terrorAttacks) =\r\n" +
"if terrorAttacks = 0 then 1/21 else 1/21; // uniform\r\n" +
"\r\n" +
"terrorAttacks = 1;\r\n" +
"dow = 170;\r\n" +
"//newJobs = 1;\r\n" +
"\r\n" +
"// P(newJobs) =\r\n" +
"if newJobs = 0 then 1/101 else 1/101; // uniform\r\n" +
"\r\n" +
"// P(dow) =\r\n" +
"if dow = 0 then 1/(180 - 110 + 1) else 1/(180 - 110 + 1); // uniform\r\n" +
"\r\n" +
"economyIsPoor <=> dow < 130 or newJobs < 30;\r\n" +
"\r\n" +
"economyIsGreat <=> dow > 160 or newJobs > 70;\r\n" +
"\r\n" +
"attackPerception <=> terrorAttacks > 4;\r\n" +
"\r\n" +
"// P(likeIncumbent) = \r\n" +
"if dow > 160 or newJobs > 70\r\n" +
" then if likeIncumbent > " + new Double(0.7*domainSize).intValue() + " then 0.9/(" + domainSize + " + 1) else 0.1/(" + domainSize + " + 1)\r\n" +
"else\r\n" +
"if dow < 130 or newJobs < 30\r\n" +
" then if likeIncumbent < " + new Double(0.5*domainSize).intValue() + " then 0.8/(" + domainSize + " + 1) else 0.2/(" + domainSize + " + 1)\r\n" +
" else if terrorAttacks > 4\r\n" +
" then if likeIncumbent < " + new Double(0.6*domainSize).intValue() + " then 0.9/(" + domainSize + " + 1) else 0.1/(" + domainSize + " + 1)\r\n" +
" else if likeIncumbent = 0 then 1/(" + domainSize + " + 1) else 1/(" + domainSize + " + 1); // uniform\r\n" +
"\r\n" +
"// P(likeChallenger) =\r\n" +
"if likeChallenger = 0 then 1/(" + domainSize + " + 1) else 1/(" + domainSize + " + 1);";
}
public static void main(String[] args) throws Exception {
AbstractEvaluateCLI evaluator = new EvaluationOnElectionModelCLI();
evaluator.run(args);
}
}