00001 /* 00002 * All of the documentation and software included in the 00003 * Alchemy Software is copyrighted by Stanley Kok, Parag 00004 * Singla, Matthew Richardson, Pedro Domingos, Marc 00005 * Sumner and Hoifung Poon. 00006 * 00007 * Copyright [2004-07] Stanley Kok, Parag Singla, Matthew 00008 * Richardson, Pedro Domingos, Marc Sumner and Hoifung 00009 * Poon. All rights reserved. 00010 * 00011 * Contact: Pedro Domingos, University of Washington 00012 * (pedrod@cs.washington.edu). 00013 * 00014 * Redistribution and use in source and binary forms, with 00015 * or without modification, are permitted provided that 00016 * the following conditions are met: 00017 * 00018 * 1. Redistributions of source code must retain the above 00019 * copyright notice, this list of conditions and the 00020 * following disclaimer. 00021 * 00022 * 2. Redistributions in binary form must reproduce the 00023 * above copyright notice, this list of conditions and the 00024 * following disclaimer in the documentation and/or other 00025 * materials provided with the distribution. 00026 * 00027 * 3. All advertising materials mentioning features or use 00028 * of this software must display the following 00029 * acknowledgment: "This product includes software 00030 * developed by Stanley Kok, Parag Singla, Matthew 00031 * Richardson, Pedro Domingos, Marc Sumner and Hoifung 00032 * Poon in the Department of Computer Science and 00033 * Engineering at the University of Washington". 00034 * 00035 * 4. Your publications acknowledge the use or 00036 * contribution made by the Software to your research 00037 * using the following citation(s): 00038 * Stanley Kok, Parag Singla, Matthew Richardson and 00039 * Pedro Domingos (2005). "The Alchemy System for 00040 * Statistical Relational AI", Technical Report, 00041 * Department of Computer Science and Engineering, 00042 * University of Washington, Seattle, WA. 00043 * http://www.cs.washington.edu/ai/alchemy. 00044 * 00045 * 5. Neither the name of the University of Washington nor 00046 * the names of its contributors may be used to endorse or 00047 * promote products derived from this software without 00048 * specific prior written permission. 00049 * 00050 * THIS SOFTWARE IS PROVIDED BY THE UNIVERSITY OF WASHINGTON 00051 * AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED 00052 * WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED 00053 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR 00054 * PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE UNIVERSITY 00055 * OF WASHINGTON OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, 00056 * INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL 00057 * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 00058 * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR 00059 * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON 00060 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 00061 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) 00062 * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN 00063 * IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 00064 * 00065 */ 00066 #ifndef INFERENCEARGS_H_ 00067 #define INFERENCEARGS_H_ 00068 00079 // Holds the names of the input mln files comma-separated 00080 char* ainMLNFiles = NULL; 00081 00082 // Holds closed-world non-evidence preds 00083 char* aClosedWorldPredsStr = NULL; 00084 // Holds open-world evidence preds 00085 char* aOpenWorldPredsStr = NULL; 00086 00087 // MAP Inference 00088 bool amapPos = false; 00089 bool amapAll = false; 00090 // Gibbs Sampling 00091 bool agibbsInfer = false; 00092 // MC-SAT 00093 bool amcsatInfer = false; 00094 // Simulated Tempering 00095 bool asimtpInfer = false; 00096 00097 // Lazy state or not? 00098 bool aLazy = false; 00099 // Seed for inference algorithm 00100 int aSeed = -1; 00101 // Limit in kbytes before using lazy version 00102 int aMemLimit = -1; 00103 // If true, atoms won't be deactivated to save space 00104 bool aLazyNoApprox = false; 00105 00106 // MaxWalkSat params 00107 int amwsMaxSteps = 100000; 00108 int amwsTries = 1; 00109 int amwsNumSolutions = 10; 00110 int amwsTargetWt = 0; 00111 bool amwsHard = false; 00112 int amwsHeuristic = 2; // 0 = RANDOM, 1 = BEST, 2 = TABU, 3 = SampleSat 00113 int amwsTabuLength = 10; 00114 bool amwsLazyLowState = false; 00115 00116 // SampleSat params 00117 int assSaRatio = 50; // percent of SA steps 00118 int assSaTemp = 50; // temperature/100: SA temperature 00119 bool assLateSa = false; // sa only at a plateur 00120 00121 // MCMC params 00122 int amcmcNumChains = 10; 00123 int amcmcBurnMinSteps = 100; 00124 int amcmcBurnMaxSteps = 100; 00125 int amcmcMinSteps = -1; 00126 int amcmcMaxSteps = 1000; 00127 int amcmcMaxSeconds = -1; 00128 00129 // Gibbs params 00130 double agibbsDelta = 0.05; 00131 double agibbsEpsilonError = 0.01; 00132 double agibbsFracConverged = 0.95; 00133 int agibbsWalksatType = 1; 00134 int agibbsSamplesPerTest = 100; 00135 00136 // MC-SAT params 00137 // Number of total steps (mcsat & Gibbs) for each MC-SAT step 00138 int amcsatNumStepsEveryMCSat = 1; 00139 00140 // Simulated Tempering params 00141 int asimtpSubInterval = 2; 00142 int asimtpNumST = 3; 00143 int asimtpNumSwap = 10; 00144 00145 #endif /*INFERENCEARGS_H_*/