source: java/ecj/cecj/archive/LAPCArchive.java @ 35

Last change on this file since 35 was 28, checked in by mszubert, 15 years ago

cecj - coEvolutionary Computation in Java with additional games package

  • Property svn:eol-style set to native
  • Property svn:keywords set to Id Revision
File size: 3.4 KB
Line 
1package cecj.archive;
2
3import java.util.ArrayList;
4import java.util.HashSet;
5import java.util.List;
6import java.util.Set;
7
8import ec.EvolutionState;
9import ec.Individual;
10import ec.util.Parameter;
11
12public class LAPCArchive extends ParetoCoevolutionArchive {
13
14        private static final String P_NUM_LAYERS = "num-layers";
15
16        private int numLayers;
17
18        private List<List<Individual>> layers;
19
20        @Override
21        public void setup(EvolutionState state, Parameter base) {
22                super.setup(state, base);
23
24                Parameter numLayersParameter = base.push(P_NUM_LAYERS);
25                numLayers = state.parameters.getInt(numLayersParameter, null, 1);
26                if (numLayers <= 0) {
27                        state.output.fatal("Number of LAPCA layers must be > 0.\n");
28                }
29
30                layers = new ArrayList<List<Individual>>(numLayers);
31        }
32
33        /*
34         * It is implemented in a IPCA-like way. Another method is to extend both existing archives by
35         * new individuals, then find first n layers of candidates with respect to all tests in the
36         * archive and in the population and finally select necessary tests making distinctions between
37         * layers.
38         */
39        @Override
40        protected void submit(EvolutionState state, List<Individual> candidates,
41                        List<Individual> cArchive, List<Individual> tests, List<Individual> tArchive) {
42                List<Individual> testsCopy = new ArrayList<Individual>(tests);
43                List<Individual> usefulTests;
44
45                for (Individual candidate : candidates) {
46                        if (isUseful(state, candidate, cArchive, tArchive, testsCopy)) {
47                                usefulTests = findUsefulTests(state, candidate, cArchive, tArchive, testsCopy);
48
49                                cArchive.add(candidate);
50                                tArchive.addAll(usefulTests);
51                                testsCopy.removeAll(usefulTests);
52                        }
53                }
54
55                maintainLayers(state, cArchive, tArchive);
56                updateTestArchive(state, tArchive);
57        }
58
59        private void updateTestArchive(EvolutionState state, List<Individual> tArchive) {
60                Set<Individual> tset = new HashSet<Individual>();
61                tset.addAll(findDistinguishingTests(state, layers.get(0), layers.get(0), tArchive));
62                for (int l = 1; l < numLayers; l++) {
63                        tset.addAll(findDistinguishingTests(state, layers.get(l - 1), layers.get(l), tArchive));
64                }
65
66                tArchive.clear();
67                tArchive.addAll(tset);
68        }
69
70        private List<Individual> findDistinguishingTests(EvolutionState state, List<Individual> layer1,
71                        List<Individual> layer2, List<Individual> tests) {
72                List<Individual> distinguishingTests = new ArrayList<Individual>();
73                for (Individual candidate1 : layer1) {
74                        for (Individual candidate2 : layer2) {
75                                if (candidate1.equals(candidate2))
76                                        continue;
77                                Individual test = findUsefulTest(state, candidate1, candidate2, tests);
78                                if ((test != null) && (!distinguishingTests.contains(test))) {
79                                        distinguishingTests.add(test);
80                                }
81                        }
82                }
83                return distinguishingTests;
84        }
85
86        private void maintainLayers(EvolutionState state, List<Individual> cArchive,
87                        List<Individual> tArchive) {
88                List<Individual> cArchiveCopy = new ArrayList<Individual>(cArchive);
89                for (int layer = 0; layer < numLayers; layer++) {
90                        List<Individual> frontPareto = findNonDominatedCandidates(state, cArchiveCopy, tArchive);
91                        layers.set(layer, frontPareto);
92                        cArchiveCopy.removeAll(frontPareto);
93                }
94                cArchive.removeAll(cArchiveCopy);
95        }
96
97        private List<Individual> findNonDominatedCandidates(EvolutionState state,
98                        List<Individual> cArchive, List<Individual> tArchive) {
99                List<Individual> result = new ArrayList<Individual>();
100                for (Individual candidate : cArchive) {
101                        if (!isDominated(state, candidate, cArchive, tArchive)) {
102                                result.add(candidate);
103                        }
104                }
105                return result;
106        }
107
108}
Note: See TracBrowser for help on using the repository browser.