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Stop using Arena type since everything can be GC'd easily

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This commit is contained in:
Asriel Camora
2023-06-21 09:12:45 -07:00
parent 5189ef5d74
commit 270963dd4a
5 changed files with 97 additions and 114 deletions
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Solver/Crafty/Arena.cs
-39
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@@ -1,39 +0,0 @@
using System.Runtime.CompilerServices;
namespace Craftimizer.Solver.Crafty;
public class Arena<T> where T : struct
{
public readonly struct Node
{
public readonly T State;
public readonly List<int> Children;
public readonly int Parent;
public Node(T state, int parent)
{
State = state;
Children = new();
Parent = parent;
}
}
private readonly List<Node> nodes = new();
public Arena(T initialState = default)
{
nodes.Add(new(initialState, -1));
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public int Insert(int parentIndex, T state)
{
var index = nodes.Count;
nodes.Add(new(state, parentIndex));
nodes[parentIndex].Children.Add(index);
return index;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public Node Get(int index) => nodes[index];
}
Solver/Crafty/ArenaNode.cs
+25
View File
@@ -0,0 +1,25 @@
using System.Runtime.CompilerServices;
namespace Craftimizer.Solver.Crafty;
public class ArenaNode<T> where T : struct
{
public readonly T State;
public readonly List<ArenaNode<T>> Children;
public readonly ArenaNode<T>? Parent;
public ArenaNode(T state, ArenaNode<T>? parent = null)
{
State = state;
Children = new();
Parent = parent;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public ArenaNode<T> Add(T state)
{
var node = new ArenaNode<T>(state, this);
Children.Add(node);
return node;
}
}
Solver/Crafty/SimulationNode.cs
+13 -5
View File
@@ -5,18 +5,26 @@ namespace Craftimizer.Solver.Crafty;
public readonly struct SimulationNode
{
public SimulationState State { get; init; }
public ActionType? Action { get; init; }
public CompletionState SimulationCompletionState { get; init; }
public readonly SimulationState State;
public readonly ActionType? Action;
public readonly CompletionState SimulationCompletionState;
public readonly NodeData Data;
public CompletionState CompletionState =>
Data.AvailableActions.Count == 0 && SimulationCompletionState == CompletionState.Incomplete ?
CompletionState.NoMoreActions :
SimulationCompletionState;
public NodeData Data { get; init; }
public bool IsComplete => CompletionState != CompletionState.Incomplete;
public SimulationNode(SimulationState state, ActionType? action, CompletionState completionState, NodeData data)
{
State = state;
Action = action;
SimulationCompletionState = completionState;
Data = data;
}
public float? CalculateScore()
{
if (CompletionState != CompletionState.ProgressComplete)
Solver/Crafty/Solver.cs
+58 -69
View File
@@ -3,6 +3,7 @@ using Craftimizer.Simulator.Actions;
using System.Numerics;
using System.Runtime.CompilerServices;
using System.Runtime.InteropServices;
using Node = Craftimizer.Solver.Crafty.ArenaNode<Craftimizer.Solver.Crafty.SimulationNode>;
namespace Craftimizer.Solver.Crafty;
@@ -10,11 +11,11 @@ namespace Craftimizer.Solver.Crafty;
public class Solver
{
public Simulator Simulator;
public Arena<SimulationNode> Tree;
public Node RootNode;
public Random Random => Simulator.Input.Random;
// public Random Random => Simulator.Input.Random;
public const int Iterations = 50000;
public const int Iterations = 30000;
public const float ScoreStorageThreshold = 1f;
public const float MaxScoreWeightingConstant = 0.1f;
public const float ExplorationConstant = 4f;
@@ -23,13 +24,12 @@ public class Solver
public Solver(SimulationState state, bool strict)
{
Simulator = new(state);
Tree = new(new()
{
State = state,
Action = null,
SimulationCompletionState = Simulator.CompletionState,
Data = new() { AvailableActions = Simulator.AvailableActionsHeuristic(strict) }
});
RootNode = new(new(
state,
null,
Simulator.CompletionState,
new() { AvailableActions = Simulator.AvailableActionsHeuristic(strict) }
));
}
public Solver(SimulationInput input, bool strict) : this(new SimulationState(input), strict)
@@ -39,37 +39,34 @@ public class Solver
private SimulationNode Execute(SimulationState state, ActionType action, bool strict)
{
(_, var newState) = Simulator.Execute(state, action);
return new()
{
State = newState,
Action = action,
SimulationCompletionState = Simulator.CompletionState,
Data = new() { AvailableActions = Simulator.AvailableActionsHeuristic(strict) }
};
return new(
newState,
action,
Simulator.CompletionState,
new() { AvailableActions = Simulator.AvailableActionsHeuristic(strict) }
);
}
public (int Index, CompletionState State) ExecuteActions(int startIndex, ReadOnlySpan<ActionType> actions, bool strict = false)
public (Node EndNode, CompletionState State) ExecuteActions(Node startNode, ReadOnlySpan<ActionType> actions, bool strict = false)
{
var currentIndex = startIndex;
foreach (var action in actions)
{
var node = Tree.Get(currentIndex).State;
if (node.IsComplete)
return (currentIndex, node.CompletionState);
var state = startNode.State;
if (state.IsComplete)
return (startNode, state.CompletionState);
if (!node.Data.AvailableActions.HasAction(action))
return (currentIndex, CompletionState.InvalidAction);
node.Data.AvailableActions.RemoveAction(action);
if (!state.Data.AvailableActions.HasAction(action))
return (startNode, CompletionState.InvalidAction);
state.Data.AvailableActions.RemoveAction(action);
currentIndex = Tree.Insert(currentIndex, Execute(node.State, action, strict));
startNode = startNode.Add(Execute(state.State, action, strict));
}
var currentNode = Tree.Get(currentIndex).State;
return (currentIndex, currentNode.CompletionState);
return (startNode, startNode.State.CompletionState);
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static int RustMaxBy(ReadOnlySpan<int> source, Func<int, float> into)
private static T RustMaxBy<T>(ReadOnlySpan<T> source, Func<T, float> into)
{
var max = 0;
var maxV = into(source[0]);
@@ -97,7 +94,7 @@ public class Solver
(length + (Vector<float>.Count - 1)) & ~(Vector<float>.Count - 1);
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private int EvalBestChild(float parentVisits, ReadOnlySpan<int> children)
private Node EvalBestChild(float parentVisits, ReadOnlySpan<Node> children)
{
var length = children.Length;
@@ -120,7 +117,7 @@ public class Solver
for (var j = 0; j < iterCount; ++j)
{
var node = Tree.Get(children[i + j]).State.Data.Scores;
var node = children[i + j].State.Data.Scores;
scoreSums[j] = node.ScoreSum;
visits[j] = node.Visits;
maxScores[j] = node.MaxScore;
@@ -140,46 +137,42 @@ public class Solver
return children[max];
}
public int Select(int selectedIndex)
public Node Select(Node selectedNode)
{
while (true)
{
var selectedNode = Tree.Get(selectedIndex);
var expandable = selectedNode.State.Data.AvailableActions.Count != 0;
var likelyTerminal = selectedNode.Children.Count == 0;
if (expandable || likelyTerminal)
{
return selectedIndex;
}
return selectedNode;
// select the node with the highest score
selectedIndex = EvalBestChild(selectedNode.State.Data.Scores.Visits, CollectionsMarshal.AsSpan(selectedNode.Children));
selectedNode = EvalBestChild(selectedNode.State.Data.Scores.Visits, CollectionsMarshal.AsSpan(selectedNode.Children));
}
}
public (int Index, CompletionState State, float Score) ExpandAndRollout(int initialIndex)
public (Node ExpandedNode, CompletionState State, float Score) ExpandAndRollout(Node initialNode)
{
var initialState = initialNode.State;
// expand once
var initialNode = Tree.Get(initialIndex).State;
if (initialNode.IsComplete)
return (initialIndex, initialNode.CompletionState, initialNode.CalculateScore() ?? 0);
if (initialState.IsComplete)
return (initialNode, initialState.CompletionState, initialState.CalculateScore() ?? 0);
var randomIdx = Random.Next(initialNode.Data.AvailableActions.Count);
var randomAction = initialNode.Data.AvailableActions.ElementAt(randomIdx);
initialNode.Data.AvailableActions.RemoveAction(randomAction);
var expandedState = Execute(initialNode.State, randomAction, true);
var expandedIndex = Tree.Insert(initialIndex, expandedState);
var randomIdx = 0;// Random.Next(initialState.Data.AvailableActions.Count);
var randomAction = initialState.Data.AvailableActions.ElementAt(randomIdx);
initialState.Data.AvailableActions.RemoveAction(randomAction);
var expandedState = Execute(initialState.State, randomAction, true);
var expandedNode = initialNode.Add(expandedState);
// playout to a terminal state
var currentState = Tree.Get(expandedIndex).State;
var currentState = expandedNode.State;
byte actionCount = 0;
Span<ActionType> actions = stackalloc ActionType[MaxStepCount];
while (true)
{
if (currentState.IsComplete)
break;
randomIdx = Random.Next(currentState.Data.AvailableActions.Count);
randomIdx = 0;// Random.Next(currentState.Data.AvailableActions.Count);
randomAction = currentState.Data.AvailableActions.ElementAt(randomIdx);
actions[actionCount++] = randomAction;
currentState = Execute(currentState.State, randomAction, true);
@@ -189,50 +182,46 @@ public class Solver
var score = currentState.CalculateScore() ?? 0;
if (currentState.CompletionState == CompletionState.ProgressComplete)
{
if (score >= ScoreStorageThreshold && score >= Tree.Get(0).State.Data.Scores.MaxScore)
if (score >= ScoreStorageThreshold && score >= RootNode.State.Data.Scores.MaxScore)
{
Console.WriteLine("DONE!");
(var terminalIndex, _) = ExecuteActions(expandedIndex, actions[..actionCount], true);
return (terminalIndex, currentState.CompletionState, score);
(var terminalNode, _) = ExecuteActions(expandedNode, actions[..actionCount], true);
return (terminalNode, currentState.CompletionState, score);
}
}
return (expandedIndex, currentState.CompletionState, score);
return (expandedNode, currentState.CompletionState, score);
}
public void Backpropagate(int startIndex, int targetIndex, float score)
public static void Backpropagate(Node startNode, Node targetNode, float score)
{
var currentIndex = startIndex;
while (true)
{
var currentNode = Tree.Get(currentIndex);
currentNode.State.Data.Scores.Visit(score);
startNode.State.Data.Scores.Visit(score);
if (currentIndex == targetIndex)
if (startNode == targetNode)
break;
currentIndex = currentNode.Parent;
startNode = startNode.Parent!;
}
}
public void Search(int startIndex)
public void Search(Node startNode)
{
for (var i = 0; i < Iterations; i++)
{
var selectedIndex = Select(startIndex);
var (endIndex, _, score) = ExpandAndRollout(selectedIndex);
var selectedNode = Select(startNode);
var (endNode, _, score) = ExpandAndRollout(selectedNode);
Backpropagate(endIndex, startIndex, score);
Backpropagate(endNode, startNode, score);
}
}
public (List<ActionType> Actions, SimulationNode Node) Solution()
{
var actions = new List<ActionType>();
var node = Tree.Get(0);
var node = RootNode;
while (node.Children.Count != 0)
{
var next_index = RustMaxBy(CollectionsMarshal.AsSpan(node.Children), n => Tree.Get(n).State.Data.Scores.MaxScore);
node = Tree.Get(next_index);
node = RustMaxBy<Node>(CollectionsMarshal.AsSpan(node.Children), n => n.State.Data.Scores.MaxScore);
if (node.State.Action != null)
actions.Add(node.State.Action.Value);
}
@@ -247,7 +236,7 @@ public class Solver
var solver = new Solver(state, true);
while (!solver.Simulator.IsComplete)
{
solver.Search(0);
solver.Search(solver.RootNode);
var (solution_actions, solution_node) = solver.Solution();
if (solution_node.Data.Scores.MaxScore >= 1.0)
@@ -271,7 +260,7 @@ public class Solver
public static (List<ActionType> Actions, SimulationState State) SearchOneshot(SimulationInput input)
{
var solver = new Solver(input, false);
solver.Search(0);
solver.Search(solver.RootNode);
var (solution_actions, solution_node) = solver.Solution();
return (solution_actions, solution_node.State);
}