blob: 527e8ce742dad1a5d325c2620b9c252488fabf8d (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
|
package ch.epfl.maze.physical.zoo;
import ch.epfl.maze.physical.Animal;
import ch.epfl.maze.physical.ProbabilisticAnimal;
import ch.epfl.maze.util.Direction;
import ch.epfl.maze.util.Vector2D;
import java.util.ArrayList;
import java.util.List;
import java.util.Set;
import java.util.stream.Collectors;
/**
* Hamster A.I. that remembers the previous choice it has made and the dead ends
* it has already met.
*
* @author EPFL
* @author Pacien TRAN-GIRARD
*/
public class Hamster extends ProbabilisticAnimal {
private final List<Vector2D> deadPaths;
/**
* Constructs a hamster with a starting position.
*
* @param position Starting position of the hamster in the labyrinth
*/
public Hamster(Vector2D position) {
super(position);
this.deadPaths = new ArrayList<>();
}
/**
* Discard directions known to lead to dead ends.
*
* @param choices A set of choices
* @return A set of smart choices
*/
private Set<Direction> excludeDeadPaths(Set<Direction> choices) {
return choices
.stream()
.filter(dir -> !this.deadPaths.contains(this.getPosition().addDirectionTo(dir)))
.collect(Collectors.toSet());
}
/**
* Moves without retracing directly its steps and by avoiding the dead-ends
* it learns during its journey.
*/
@Override
public Direction move(Set<Direction> choices) {
Set<Direction> smartChoices = this.excludeDeadPaths(choices);
if (smartChoices.size() == 1) this.deadPaths.add(this.getPosition()); // dead end
return super.move(smartChoices);
}
@Override
public Animal copy() {
return new Hamster(this.getPosition());
}
}
|