Simon O'Shea
262 lines
6.7 KiB
C#
262 lines
6.7 KiB
C#
using System;
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using System.Collections;
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using System.Collections.Generic;
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using UnityEngine;
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class Node : IComparable<Node>
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{
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// helper variables just to make indexing arrays easier to read
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public static int row = 0;
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public static int col = 1;
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Node parent;
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int[] agent;
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List<int[]> samples;
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char lastMove; // for output/animation
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int distanceTraveled; // for calculating f(n) value
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double heuristic;
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double fn; // distance traveled + heuristic value
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bool canSample; // for expansion
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// construct node :)
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public Node(Node parent, int[] agent, List<int[]> samples, char lastMove, int distanceTraveled, double heuristic)
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{
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this.parent = parent;
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this.agent = agent;
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this.samples = new ArrayList<int[]>(samples);
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this.lastMove = lastMove;
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this.distanceTraveled = distanceTraveled;
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this.heuristic = heuristic;
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this.fn = distanceTraveled + heuristic;
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}
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// determine valid moves and collect children to be sent back to search
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public List<Node> expand(int depth)
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{
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List<Node> children = new ArrayList<Node>();
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if (this.distanceTraveled >= depth && depth != -1)
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return children;
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// document expansion of node and get ready to collect this node's children
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SampleWorld.expansions++;
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int[] onSample = new int[2];
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// since this state is being currently visited (expanded), put in closed list
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SampleWorld.closed.add(this.getState());
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////////////////////////////////////
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// BEGIN CHECKING FOR VALID MOVES //
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////////////////////////////////////
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// store coordinates for all potential moves to be checked
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int[] up = { this.agent[row] - 1, this.agent[col] };
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int[] down = { this.agent[row] + 1, this.agent[col] };
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int[] left = { this.agent[row], this.agent[col] - 1 };
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int[] right = { this.agent[row], this.agent[col] + 1 };
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// make sure going up doesn't go outside world-bounds or into obstacle
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if (isOpen(up))
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{
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// if move is valid, create that new node/state and document
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Node child = new Node(this, up, this.samples, 'U', this.distanceTraveled + 1, this.heuristic);
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SampleWorld.nodesGenerated++;
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// make sure that we have not already made that move
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if (!child.getState().inClosed())
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children.add(child);
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}
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// same idea but for the different potential moves
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if (isOpen(down))
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{
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Node child = new Node(this, down, this.samples, 'D', this.distanceTraveled + 1, this.heuristic);
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SampleWorld.nodesGenerated++;
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if (!child.getState().inClosed())
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children.add(child);
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}
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if (isOpen(left))
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{
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Node child = new Node(this, left, this.samples, 'L', this.distanceTraveled + 1, this.heuristic);
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SampleWorld.nodesGenerated++;
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if (!child.getState().inClosed())
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children.add(child);
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}
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if (isOpen(right))
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{
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Node child = new Node(this, right, this.samples, 'R', this.distanceTraveled + 1, this.heuristic);
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SampleWorld.nodesGenerated++;
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if (!child.getState().inClosed())
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children.add(child);
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}
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// CHECK IF CAN SAMPLE
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onSample = canSample();
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if (onSample[0] == 1)
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{
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Node child = new Node(this, this.agent, this.samples, 'S', this.distanceTraveled + 1, this.heuristic);
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child.samples.remove(onSample[1]);
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SampleWorld.nodesGenerated++;
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children.add(child);
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}
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return children;
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}
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// helper for expand, verifies whether potential move is legal
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public boolean isOpen(int[] position)
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{
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// check that agent is not trying to move into an obstacle
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for (int i = 0; i < SampleWorld.obstacles.size(); i++)
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{
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if (Arrays.compare(SampleWorld.obstacles.get(i), position) == 0)
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return false;
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}
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// check that agent is not stepping out of the world
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if (!((position[row] >= 0) && (position[row] <= SampleWorld.worldRows - 1) && (position[col] >= 0) && (position[col] <= SampleWorld.worldCols - 1)))
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return false;
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return true;
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}
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// returns the coordinates of the sample closest to the agent's current location
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public int[] nearestSample()
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{
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if (samples.size() == 0)
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return agent;
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int[] s = samples.get(0);
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double lowest = distance(agent, samples.get(0));
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double distance;
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for (int i = 1; i < samples.size(); i++)
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{
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distance = distance(agent, samples.get(i));
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if (distance < lowest)
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{
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lowest = distance;
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s = samples.get(i);
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}
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}
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return s;
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}
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// helper function for nearestSample()
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public static double distance(int[] a, int[] b)
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{ // _________________________
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// distance between 2D points = √(y2 - y1)^2 + (x2 - x1)^2
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double total = (((b[row] - a[row]) * (b[row] - a[row])) + ((b[col] - a[col]) * (b[col] - a[col])));
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total = Math.sqrt(total);
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return total;
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}
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// helper function for h2
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/////////////////////////////
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// returns two pieces of information if true:
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// [0] is 1 to indicate agent can sample
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// [1] is the index of the valid sample in the list
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public int[] canSample()
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{
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// default to false
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int[] result = new int[2];
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result[0] = 0;
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result[1] = -1;
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for (int i = 0; i < this.samples.size(); i++)
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{
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if ((this.agent[row] == samples.get(i)[row]) && (this.agent[col] == samples.get(i)[col]))
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{
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result[0] = 1;
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result[1] = i;
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return result;
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}
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}
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return result;
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}
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// returns only the dynamic information directly related to the Node's state.
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// we need a way to extract just this information for the sake of our closed list
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public State getState()
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{
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return new State(this.agent, this.samples);
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}
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// we use to override comparisons for priorityQueues so that our heuristic calculations are actually used
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@Override
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public int compareTo(Node other)
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{
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if (this.fn > other.fn)
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return 1;
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else
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return -1;
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}
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}
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// helper class for Node
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class NodeComparator implements Comparator<Node>
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{
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// used to sort nodes based on sum of distance traveled + heuristic estimation of work left
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@Override
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public int compare(Node a, Node b)
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{
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if (a.fn > b.fn)
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return 1;
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else
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return -1;
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}
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}
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// helper class for Node
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class State
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{
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int[] agent;
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int[][] samples;
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public State(int[] agent, List<int[]> samples)
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{
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this.agent = agent;
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this.samples = new int[samples.size()][];
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// convert List<int[]> into 2D array of ints [][]
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for (int i = 0; i < samples.size(); i++)
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{
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this.samples[i] = samples.get(i).clone();
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}
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}
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public boolean inClosed()
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{
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for (int i = 0; i < SampleWorld.closed.size(); i++)
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{
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if (this.equals(SampleWorld.closed.get(i)))
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{
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return true;
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}
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}
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return false;
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}
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public boolean equals(State other)
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{
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if (this.samples.length != other.samples.length)
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return false;
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if (Arrays.compare(this.agent, other.agent) != 0)
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return false;
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for (int i = 0; i < this.samples.length; i++)
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{
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if (Arrays.compare(this.samples[i], other.samples[i]) != 0)
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return false;
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}
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return true;
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}
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}
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