1
|
|
|
package it.cnr.istc.pst.platinum.ai.deliberative.strategy; |
2
|
|
|
|
3
|
|
|
import java.util.Map; |
4
|
|
|
|
5
|
|
|
import it.cnr.istc.pst.platinum.ai.deliberative.solver.SearchSpaceNode; |
6
|
|
|
import it.cnr.istc.pst.platinum.ai.framework.domain.component.DomainComponent; |
7
|
|
|
|
8
|
|
|
/** |
9
|
|
|
* |
10
|
|
|
* @author alessandro |
11
|
|
|
* |
12
|
|
|
*/ |
13
|
|
|
public class StandardDeviationMinimizationSearchStrategy extends SearchStrategy { |
14
|
|
|
|
15
|
|
|
/** |
16
|
|
|
* |
17
|
|
|
*/ |
18
|
|
|
protected StandardDeviationMinimizationSearchStrategy() { |
19
|
|
|
super("TimelineSDMinimizationSearchStrategy"); |
20
|
|
|
} |
21
|
|
|
|
22
|
|
|
/** |
23
|
|
|
* |
24
|
|
|
*/ |
25
|
|
|
@Override |
26
|
|
|
public void enqueue(SearchSpaceNode node) { |
27
|
|
|
|
28
|
|
|
// compute a pessimistic estimation of flaw resolution cost |
29
|
|
|
Map<DomainComponent, Double[]> h = this.computeHeuristicCost(node); |
30
|
|
|
// set heuristic estimation |
31
|
|
|
node.setHeuristicCost(h); |
32
|
|
|
// add the node to the priority queue |
33
|
|
|
this.fringe.offer(node); |
34
|
|
|
} |
35
|
|
|
|
36
|
|
|
/** |
37
|
|
|
* |
38
|
|
|
*/ |
39
|
|
|
@Override |
40
|
|
|
public int compare(SearchSpaceNode o1, SearchSpaceNode o2) { |
41
|
|
|
|
42
|
|
|
// get plan horizon |
43
|
|
|
long horizon = this.pdb.getHorizon(); |
44
|
|
|
|
45
|
|
|
double sd1 = this.standardDevitation(horizon, o1); |
46
|
|
|
double sd2 = this.standardDevitation(horizon, o2); |
47
|
|
|
|
48
|
|
|
// greedy search checking standard deviation to the horizon |
49
|
|
|
return o1.getDepth() > o2.getDepth() ? -1 : o1.getDepth() < o2.getDepth() ? 1 : |
50
|
|
|
// check standard deviations |
51
|
|
|
sd1 < sd2 ? -1 : sd1 > sd2 ? 1 : |
52
|
|
|
0; |
53
|
|
|
} |
54
|
|
|
|
55
|
|
|
/** |
56
|
|
|
* |
57
|
|
|
* @param horizon |
58
|
|
|
* @param node |
59
|
|
|
* @return |
60
|
|
|
*/ |
61
|
|
|
public double standardDevitation(long horizon, SearchSpaceNode node) { |
62
|
|
|
|
63
|
|
|
// initialize standard deviation with horizon |
64
|
|
|
double sd = horizon; |
65
|
|
|
|
66
|
|
|
// get estimated makespan of the plan |
67
|
|
|
Map<DomainComponent, Double[]> mk = node.getEstimatedMakespan(); |
68
|
|
|
double N = mk.keySet().size(); |
69
|
|
|
double quadSum = 0; |
70
|
|
|
for (DomainComponent comp : mk.keySet()) { |
|
|
|
|
71
|
|
|
|
72
|
|
|
quadSum += Math.pow((mk.get(comp)[0] - horizon), 2.0); |
73
|
|
|
} |
74
|
|
|
|
75
|
|
|
// check data |
76
|
|
|
if (N > 0 && quadSum > 0) { |
77
|
|
|
// compute standard deviation |
78
|
|
|
sd = Math.sqrt(quadSum / N); |
79
|
|
|
} |
80
|
|
|
|
81
|
|
|
// return standard deviation |
82
|
|
|
return sd; |
83
|
|
|
|
84
|
|
|
} |
85
|
|
|
|
86
|
|
|
} |
87
|
|
|
|