gamecodebook/Chapter04/Search.cpp

#include <vector>
#include <queue>
#include <iostream>
#include <unordered_map>

struct GraphNode
{
	// Adjacency list
	std::vector<GraphNode*> mAdjacent;
};

struct Graph
{
	// A graph contains nodes
	std::vector<GraphNode*> mNodes;
};

struct WeightedEdge
{
	// Which nodes are connected by this edge?
	struct WeightedGraphNode* mFrom;
	struct WeightedGraphNode* mTo;
	// Weight of this edge
	float mWeight;
};

struct WeightedGraphNode
{
	std::vector<WeightedEdge*> mEdges;
};

struct WeightedGraph
{
	std::vector<WeightedGraphNode*> mNodes;
};

struct GBFSScratch
{
	const WeightedEdge* mParentEdge = nullptr;
	float mHeuristic = 0.0f;
	bool mInOpenSet = false;
	bool mInClosedSet = false;
};

using GBFSMap =
std::unordered_map<const WeightedGraphNode*, GBFSScratch>;

struct AStarScratch
{
	const WeightedEdge* mParentEdge = nullptr;
	float mHeuristic = 0.0f;
	float mActualFromStart = 0.0f;
	bool mInOpenSet = false;
	bool mInClosedSet = false;
};

using AStarMap =
std::unordered_map<const WeightedGraphNode*, AStarScratch>;

float ComputeHeuristic(const WeightedGraphNode* a, const WeightedGraphNode* b)
{
	return 0.0f;
}

bool AStar(const WeightedGraph& g, const WeightedGraphNode* start,
	const WeightedGraphNode* goal, AStarMap& outMap)
{
	std::vector<const WeightedGraphNode*> openSet;

	// Set current node to start, and mark in closed set
	const WeightedGraphNode* current = start;
	outMap[current].mInClosedSet = true;

	do
	{
		// Add adjacent nodes to open set
		for (const WeightedEdge* edge : current->mEdges)
		{
			const WeightedGraphNode* neighbor = edge->mTo;
			// Get scratch data for this node
			AStarScratch& data = outMap[neighbor];
			// Only check nodes that aren't in the closed set
			if (!data.mInClosedSet)
			{
				if (!data.mInOpenSet)
				{
					// Not in the open set, so parent must be current
					data.mParentEdge = edge;
					data.mHeuristic = ComputeHeuristic(neighbor, goal);
					// Actual cost is the parent's plus cost of traversing edge
					data.mActualFromStart = outMap[current].mActualFromStart +
						edge->mWeight;
					data.mInOpenSet = true;
					openSet.emplace_back(neighbor);
				}
				else
				{
					// Compute what new actual cost is if current becomes parent
					float newG = outMap[current].mActualFromStart + edge->mWeight;
					if (newG < data.mActualFromStart)
					{
						// Current should adopt this node
						data.mParentEdge = edge;
						data.mActualFromStart = newG;
					}
				}
			}
		}

		// If open set is empty, all possible paths are exhausted
		if (openSet.empty())
		{
			break;
		}

		// Find lowest cost node in open set
		auto iter = std::min_element(openSet.begin(), openSet.end(),
			[&outMap](const WeightedGraphNode* a, const WeightedGraphNode* b) {
			// Calculate f(x) for nodes a/b
			float fOfA = outMap[a].mHeuristic + outMap[a].mActualFromStart;
			float fOfB = outMap[b].mHeuristic + outMap[b].mActualFromStart;
			return fOfA < fOfB;
		});
		// Set to current and move from open to closed
		current = *iter;
		openSet.erase(iter);
		outMap[current].mInOpenSet = true;
		outMap[current].mInClosedSet = true;
	} while (current != goal);

	// Did we find a path?
	return (current == goal) ? true : false;
}

bool GBFS(const WeightedGraph& g, const WeightedGraphNode* start,
	const WeightedGraphNode* goal, GBFSMap& outMap)
{
	std::vector<const WeightedGraphNode*> openSet;

	// Set current node to start, and mark in closed set
	const WeightedGraphNode* current = start;
	outMap[current].mInClosedSet = true;

	do
	{
		// Add adjacent nodes to open set
		for (const WeightedEdge* edge : current->mEdges)
		{
			// Get scratch data for this node
			GBFSScratch& data = outMap[edge->mTo];
			// Add it only if it's not in the closed set
			if (!data.mInClosedSet)
			{
				// Set the adjacent node's parent edge
				data.mParentEdge = edge;
				if (!data.mInOpenSet)
				{
					// Compute the heuristic for this node, and add to open set
					data.mHeuristic = ComputeHeuristic(edge->mTo, goal);
					data.mInOpenSet = true;
					openSet.emplace_back(edge->mTo);
				}
			}
		}

		// If open set is empty, all possible paths are exhausted
		if (openSet.empty())
		{
			break;
		}

		// Find lowest cost node in open set
		auto iter = std::min_element(openSet.begin(), openSet.end(),
			[&outMap](const WeightedGraphNode* a, const WeightedGraphNode* b) {
			return outMap[a].mHeuristic < outMap[b].mHeuristic;
		});

		// Set to current and move from open to closed
		current = *iter;
		openSet.erase(iter);
		outMap[current].mInOpenSet = false;
		outMap[current].mInClosedSet = true;
	} while (current != goal);

	// Did we find a path?
	return (current == goal) ? true : false;
}

using NodeToParentMap =
std::unordered_map<const GraphNode*, const GraphNode*>;

bool BFS(const Graph& graph, const GraphNode* start, const GraphNode* goal, NodeToParentMap& outMap)
{
	// Whether we found a path
	bool pathFound = false;
	// Nodes to consider
	std::queue<const GraphNode*> q;
	// Enqueue the first node
	q.emplace(start);

	while (!q.empty())
	{
		// Dequeue a node
		const GraphNode* current = q.front();
		q.pop();
		if (current == goal)
		{
			pathFound = true;
			break;
		}

		// Enqueue adjacent nodes that aren't already in the queue
		for (const GraphNode* node : current->mAdjacent)
		{
			// If the parent is null, it hasn't been enqueued
			// (except for the start node)
			const GraphNode* parent = outMap[node];
			if (parent == nullptr && node != start)
			{
				// Enqueue this node, setting its parent
				outMap[node] = current;
				q.emplace(node);
			}
		}
	}

	return pathFound;
}

void testBFS()
{
	Graph g;
	for (int i = 0; i < 5; i++)
	{
		for (int j = 0; j < 5; j++)
		{
			GraphNode* node = new GraphNode;
			g.mNodes.emplace_back(node);
		}
	}

	for (int i = 0; i < 5; i++)
	{
		for (int j = 0; j < 5; j++)
		{
			GraphNode* node = g.mNodes[i * 5 + j];
			if (i > 0)
			{
				node->mAdjacent.emplace_back(g.mNodes[(i - 1) * 5 + j]);
			}
			if (i < 4)
			{
				node->mAdjacent.emplace_back(g.mNodes[(i + 1) * 5 + j]);
			}
			if (j > 0)
			{
				node->mAdjacent.emplace_back(g.mNodes[i * 5 + j - 1]);
			}
			if (j < 4)
			{
				node->mAdjacent.emplace_back(g.mNodes[i * 5 + j + 1]);
			}
		}
	}

	NodeToParentMap map;
	bool found = BFS(g, g.mNodes[0], g.mNodes[9], map);
	std::cout << found << '\n';
}

void testHeuristic(bool useAStar)
{
	WeightedGraph g;
	for (int i = 0; i < 5; i++)
	{
		for (int j = 0; j < 5; j++)
		{
			WeightedGraphNode* node = new WeightedGraphNode;
			g.mNodes.emplace_back(node);
		}
	}

	for (int i = 0; i < 5; i++)
	{
		for (int j = 0; j < 5; j++)
		{
			WeightedGraphNode* node = g.mNodes[i * 5 + j];
			if (i > 0)
			{
				WeightedEdge* e = new WeightedEdge;
				e->mFrom = node;
				e->mTo = g.mNodes[(i - 1) * 5 + j];
				e->mWeight = 1.0f;
				node->mEdges.emplace_back(e);
			}
			if (i < 4)
			{
				WeightedEdge* e = new WeightedEdge;
				e->mFrom = node;
				e->mTo = g.mNodes[(i + 1) * 5 + j];
				e->mWeight = 1.0f;
				node->mEdges.emplace_back(e);
			}
			if (j > 0)
			{
				WeightedEdge* e = new WeightedEdge;
				e->mFrom = node;
				e->mTo = g.mNodes[i * 5 + j - 1];
				e->mWeight = 1.0f;
				node->mEdges.emplace_back(e);
			}
			if (j < 4)
			{
				WeightedEdge* e = new WeightedEdge;
				e->mFrom = node;
				e->mTo = g.mNodes[i * 5 + j + 1];
				e->mWeight = 1.0f;
				node->mEdges.emplace_back(e);
			}
		}
	}
	bool found = false;
	if (useAStar)
	{
		AStarMap map;
		found = AStar(g, g.mNodes[0], g.mNodes[9], map);
	}
	else
	{
		GBFSMap map;
		found = GBFS(g, g.mNodes[0], g.mNodes[9], map);
	}
	std::cout << found << '\n';
}

struct GameState
{
	// (For tic-tac-toe, array of board)
	enum SquareState { Empty, X, O };
	SquareState mBoard[3][3];
};

struct GTNode
{
	// Children nodes
	std::vector<GTNode*> mChildren;
	// State of game
	GameState mState;
};

void GenStates(GTNode* root, bool xPlayer)
{
	for (int i = 0; i < 3; i++)
	{
		for (int j = 0; j < 3; j++)
		{
			if (root->mState.mBoard[i][j] == GameState::Empty)
			{
				GTNode* node = new GTNode;
				root->mChildren.emplace_back(node);
				node->mState = root->mState;
				node->mState.mBoard[i][j] = xPlayer ? GameState::X : GameState::O;
				GenStates(node, !xPlayer);
			}
		}
	}
}

float GetScore(const GameState& state)
{
	// Are any of the rows the same?
	for (int i = 0; i < 3; i++)
	{
		bool same = true;
		GameState::SquareState v = state.mBoard[i][0];
		for (int j = 1; j < 3; j++)
		{
			if (state.mBoard[i][j] != v)
			{
				same = false;
			}
		}

		if (same)
		{
			if (v == GameState::X)
			{
				return 1.0f;
			}
			else
			{
				return -1.0f;
			}
		}
	}

	// Are any of the columns the same?
	for (int j = 0; j < 3; j++)
	{
		bool same = true;
		GameState::SquareState v = state.mBoard[0][j];
		for (int i = 1; i < 3; i++)
		{
			if (state.mBoard[i][j] != v)
			{
				same = false;
			}
		}

		if (same)
		{
			if (v == GameState::X)
			{
				return 1.0f;
			}
			else
			{
				return -1.0f;
			}
		}
	}

	// What about diagonals?
	if (((state.mBoard[0][0] == state.mBoard[1][1]) &&
		(state.mBoard[1][1] == state.mBoard[2][2])) ||
		((state.mBoard[2][0] == state.mBoard[1][1]) &&
		(state.mBoard[1][1] == state.mBoard[0][2])))
	{
		if (state.mBoard[1][1] == GameState::X)
		{
			return 1.0f;
		}
		else
		{
			return -1.0f;
		}
	}
	// We tied
	return 0.0f;
}

float MinPlayer(const GTNode* node);

float MaxPlayer(const GTNode* node)
{
	// If this is a leaf, return score
	if (node->mChildren.empty())
	{
		return GetScore(node->mState);
	}

	float maxValue = -std::numeric_limits<float>::infinity();
	// Find the subtree with the maximum value
	for (const GTNode* child : node->mChildren)
	{
		maxValue = std::max(maxValue, MinPlayer(child));
	}
	return maxValue;
}

float MinPlayer(const GTNode* node)
{
	// If this is a leaf, return score
	if (node->mChildren.empty())
	{
		return GetScore(node->mState);
	}

	float minValue = std::numeric_limits<float>::infinity();
	// Find the subtree with the minimum value
	for (const GTNode* child : node->mChildren)
	{
		minValue = std::min(minValue, MaxPlayer(child));
	}
	return minValue;
}

const GTNode* MinimaxDecide(const GTNode* root)
{
	// Find the subtree with the maximum value, and save the choice
	const GTNode* choice = nullptr;
	float maxValue = -std::numeric_limits<float>::infinity();
	for (const GTNode* child : root->mChildren)
	{
		float v = MinPlayer(child);
		if (v > maxValue)
		{
			maxValue = v;
			choice = child;
		}
	}
	return choice;
}

float AlphaBetaMin(const GTNode* node, float alpha, float beta);

float AlphaBetaMax(const GTNode* node, float alpha, float beta)
{
	// If this is a leaf, return score
	if (node->mChildren.empty())
	{
		return GetScore(node->mState);
	}

	float maxValue = -std::numeric_limits<float>::infinity();
	// Find the subtree with the maximum value
	for (const GTNode* child : node->mChildren)
	{
		maxValue = std::max(maxValue, AlphaBetaMin(child, alpha, beta));
		if (maxValue >= beta)
		{
			return maxValue; // Beta prune
		}
		alpha = std::max(maxValue, alpha);
	}
	return maxValue;
}

float AlphaBetaMin(const GTNode* node, float alpha, float beta)
{
	// If this is a leaf, return score
	if (node->mChildren.empty())
	{
		return GetScore(node->mState);
	}

	float minValue = std::numeric_limits<float>::infinity();
	// Find the subtree with the minimum value
	for (const GTNode* child : node->mChildren)
	{
		minValue = std::min(minValue, AlphaBetaMax(child, alpha, beta));
		if (minValue <= alpha)
		{
			return minValue; // Alpha prune
		}
		beta = std::min(minValue, beta);
	}
	return minValue;
}

const GTNode* AlphaBetaDecide(const GTNode* root)
{
	// Find the subtree with the maximum value, and save the choice
	const GTNode* choice = nullptr;
	float maxValue = -std::numeric_limits<float>::infinity();
	float beta = std::numeric_limits<float>::infinity();
	for (const GTNode* child : root->mChildren)
	{
		float v = AlphaBetaMin(child, maxValue, beta);
		if (v > maxValue)
		{
			maxValue = v;
			choice = child;
		}
	}
	return choice;
}

void testTicTac()
{
	GTNode* root = new GTNode;
	root->mState.mBoard[0][0] = GameState::O;
	root->mState.mBoard[0][1] = GameState::Empty;
	root->mState.mBoard[0][2] = GameState::X;
	root->mState.mBoard[1][0] = GameState::X;
	root->mState.mBoard[1][1] = GameState::O;
	root->mState.mBoard[1][2] = GameState::O;
	root->mState.mBoard[2][0] = GameState::X;
	root->mState.mBoard[2][1] = GameState::Empty;
	root->mState.mBoard[2][2] = GameState::Empty;

	GenStates(root, true);
	const GTNode* choice = AlphaBetaDecide(root);
	std::cout << choice->mChildren.size();
}