public AI_Order(int id, EActionCode code, Vector3 position, Vector3 direction)
{
this.CharacterID = id;
this.ActionCode = code;
this.Direction = direction;
this.Position = position;
}
public AI_Action(EActionCode action_code, AI_Character caster, AI_Character target)
{
this.ActionCode = action_code;
this.Caster = caster;
this.Target = target;
this.Success = false;
}
} // ignored for events other than EventTypeDamageDealt
public AI_ParamEvent(EEventType type, int caster_id, int target_id, EActionCode action_code, float damage)
{
this.ActionCode = action_code;
this.EventType = type;
this.CasterID = caster_id;
this.TargetID = target_id;
this.Damage = damage;
}
/// <summary>
/// Gives a new order to a character. Previous orders that were not consumed are overriden.
/// </summary>
/// <param name="id"></param>
/// <param name="code">Action code</param>
/// <param name="direction">Target direction of the action (optional)</param>
/// <param name="position">Target position of the action (optional)</param>
/// <returns>Order to perform</returns>
public static AI_Order SetOrderForCharacter(int id, EActionCode code, Vector3 position, Vector3 direction)
{
lock (Orders)
{
AI_Order order = new AI_Order(id, code, position, direction);
Orders[id] = order;
return(order);
}
}
public AI_DeepLearningSystem()
{
this.IsRunning = false;
this.LastUpdateTime = 0.0f;
this.Characters = new Dictionary <int, AI_Character>();
this.Anticipation_ActionCode = EActionCode.ActionCodeNoAction;
this.Anticipation_ActionTime = 0.0f;
this.Anticipation_Probability = 0.0f;
this.LoadNetworkState();
}
/// <summary>
/// 构造一个新的协议并初始化协议头部.
/// </summary>
/// <param name="request">一级，类</param>
/// <param name="action">二级，方法</param>
/// <param name="returncode">三级，返回值</param>
public ProtocolBytes(ERequestCode request, EActionCode action, EReturnCode returncode = EReturnCode.None)
{
RequestCode = request;
ActionCode = action;
ReturnCode = returncode;
AddInt((int)RequestCode);
AddInt((int)ActionCode);
AddInt((int)ReturnCode);
}
/// <summary>
/// Trains the anticipation network.
/// </summary>
/// <param name="player">Player</param>
/// <param name="action_code">Code of the action performed</param>
public void TrainAnticipation(AI_Character player, EActionCode action_code)
{
AI_DeepLearningNetwork network;
float[] outputs = new float[(int)EActionCode.Count];
for (EActionCode code = EActionCode.ActionCodeNoAction; code < EActionCode.Count; code++)
{
outputs[(int)code] = (code == action_code) ? 1.0f : 0.0f;
}
foreach (AI_Character c in this.Characters.Values)
{
if (c.CharacterType == ECharacterType.CharacterTypeEnemy && c.IsAlive)
{
if (player.PreviousAction != null)
{
network = this.Networks_Anticipation_1[player.PreviousAction.ActionCode];
network.Learn(new float[] {
Vector3.Distance(c.Position, player.Position),
Vector3.Angle(player.Direction, c.Position - player.Position),
Vector3.Angle(c.Direction, player.Position - c.Position),
this.LastUpdateTime - player.PreviousAction.CastTime
}, outputs);
}
if (c.CurrentAction != null)
{
network = this.Networks_Anticipation_2[c.CurrentAction.ActionCode];
network.Learn(new float[] {
Vector3.Distance(c.Position, player.Position),
Vector3.Angle(player.Direction, c.Position - player.Position),
Vector3.Angle(c.Direction, player.Position - c.Position),
this.LastUpdateTime - c.CurrentAction.CastTime
}, outputs);
}
else
{
network = this.Networks_Anticipation_2[EActionCode.ActionCodeNoAction];
network.Learn(new float[] {
Vector3.Distance(c.Position, player.Position),
Vector3.Angle(player.Direction, c.Position - player.Position),
Vector3.Angle(c.Direction, player.Position - c.Position),
this.LastUpdateTime - c.CurrentAction.CastTime
}, outputs);
}
}
}
}
/// <summary>
/// Called when a character starts a new action.
/// </summary>
/// <param name="caster">Caster</param>
/// <param name="action_code">Code of the action (see EActionCode)</param>
public void OnCharacterActionStarted(AI_Character caster, EActionCode action_code)
{
Debug.Log("[AI] Action started (Caster ID: " + caster.CharacterID + ", Action Code: " + action_code + ").");
AI_Character target = null;
// Determining the target
switch (caster.CharacterType)
{
case ECharacterType.CharacterTypeEnemy:
Debug.Assert(this.Characters.ContainsKey(AI_Params.PlayerID), "[AI] Invalid player ID (" + AI_Params.PlayerID + ").");
target = this.Characters[AI_Params.PlayerID];
break;
case ECharacterType.CharacterTypePlayer:
float distance = 10000.0f;
foreach (AI_Character c in this.Characters.Values)
{
if (distance > Vector3.Distance(c.Position, caster.Position) + Mathf.Abs(Vector3.Angle(caster.Direction, c.Position - caster.Position)))
{
distance = Vector3.Distance(c.Position, caster.Position) + Mathf.Abs(Vector3.Angle(caster.Direction, c.Position - caster.Position));
target = c;
}
}
break;
}
// Registering the action
AI_Action action = caster.OnActionStarted(this.LastUpdateTime, action_code, target);
foreach (AI_Character c in this.Characters.Values)
{
if ((c.CurrentAction != null) && (c.CurrentAction.Target.CharacterID == caster.CharacterID))
{
c.CurrentAction.OnTargetActionStarted(action);
}
}
// Training anticipation network
if (caster.CharacterType == ECharacterType.CharacterTypePlayer)
{
this.TrainAnticipation(caster, action_code);
}
}
/// <summary>
/// 消息分发
/// </summary>
/// <param name="conn"></param>
/// <param name="protocolBase"></param>
private void HandleMsg(Conn conn, ProtocolBase protocolBase)
{
ERequestCode requestCode = protocolBase.RequestCode;
EActionCode actionCode = protocolBase.ActionCode;
Console.WriteLine($"收到来自[{conn.GetAddress()}]协议:[{ requestCode.ToString()}---{actionCode.ToString()}]");
BaseController controller;
if (!requestDict.TryGetValue(requestCode, out controller))
{
Console.WriteLine($"【警告】未找到Request:{requestCode.ToString()}对应的方法");
return;
}
MethodInfo method = controller.GetType().GetMethod(actionCode.ToString());
if (method == null)
{
Console.WriteLine($"【警告】未找到Action:{actionCode.ToString()}对应的方法");
return;
}
object[] objs = new object[] { conn, protocolBase };
method.Invoke(controller, objs);
}
public static void PushEvent(EEventType type, int caster_id, int target_id, EActionCode action_code)
{
PushEvent(type, caster_id, target_id, action_code, 0.0f);
}
/// <summary>
/// [Game thread] Adds information about an event that occured since the last update.
/// </summary>
/// <param name="type">Type of event (refer to the EEventType enum for valid event types)</param>
/// <param name="caster_id">ID of the caster (optional, AI_Params.UnknownID if undetermined)</param>
/// <param name="target_id">ID of the target (optional, AI_Params.UnknownID if undetermined)</param>
/// <param name="action_code">Code of the action (optional, refer to the EActionCode enum for valid action codes)</param>
/// <param name="damage">Damage dealt (optional)</param>
public static void PushEvent(EEventType type, int caster_id, int target_id, EActionCode action_code, float damage)
{
Instance.Events.Add(new AI_ParamEvent(type, caster_id, target_id, action_code, damage));
}
/// Character started an action
public AI_Action OnActionStarted(float game_time, EActionCode action_code, AI_Character target)
{
this.CurrentAction = new AI_Action(action_code, this, target);
this.CurrentAction.OnActionStarted(game_time);
return(this.CurrentAction);
}
/// <summary>
/// Thinks the orders for AI characters.
/// </summary>
public void ThinkAction()
{
Debug.Assert(this.Characters.ContainsKey(AI_Params.PlayerID), "[AI] Invalid player ID (" + AI_Params.PlayerID + ").");
AI_Character player = this.Characters[AI_Params.PlayerID];
foreach (AI_Character c in this.Characters.Values)
{
if (!c.IsPlayer && c.IsAlive && c.IsIdle)
{
AI_DeepLearningNetwork network;
float[] outputs;
float[] actions = new float[(int)EActionCode.Count];
for (EActionCode code = EActionCode.ActionCodeNoAction; code < EActionCode.Count; code++)
{
actions[(int)code] = 0.0f;
}
for (EActionCode code = EActionCode.ActionCodeNoAction; code < EActionCode.Count; code++)
{
// Action
network = this.Networks_Action[code];
outputs = network.Think(new float[] {
Vector3.Distance(c.Position, player.Position),
Vector3.Angle(c.Direction, player.Position - c.Position),
Vector3.Angle(player.Direction, c.Position - player.Position)
}, network.Variance);
actions[(int)code] = outputs[0];
// Reaction
if (player.CurrentAction != null)
{
network = this.Networks_Reaction[code][player.CurrentAction.ActionCode];
outputs = network.Think(new float[] {
Vector3.Distance(c.Position, player.Position),
Vector3.Angle(c.Direction, player.Position - c.Position),
Vector3.Angle(player.Direction, c.Position - player.Position),
this.LastUpdateTime - player.CurrentAction.CastTime
}, network.Variance);
actions[(int)code] = actions[(int)code] * outputs[0] - outputs[1];
}
else
{
network = this.Networks_Reaction[code][this.Anticipation_ActionCode];
outputs = network.Think(new float[] {
Vector3.Distance(c.Position, player.Position),
Vector3.Angle(c.Direction, player.Position - c.Position),
Vector3.Angle(player.Direction, c.Position - player.Position),
this.LastUpdateTime - this.Anticipation_ActionTime
}, network.Variance);
actions[(int)code] = actions[(int)code] * outputs[0] - outputs[1];
}
}
// Choosing the best action
float best_action_value = 0.0f;
EActionCode best_action_code = EActionCode.ActionCodeNoAction;
for (EActionCode code = EActionCode.ActionCodeNoAction; code < EActionCode.Count; code++)
{
if (best_action_value < actions[(int)code])
{
best_action_value = actions[(int)code];
best_action_code = code;
}
}
// Setting the new order
switch (best_action_code)
{
case EActionCode.ActionCodeAttackLight:
case EActionCode.ActionCodeAttackHeavy:
case EActionCode.ActionCodeGuard:
Debug.Log("[AI] Set order for character " + c.CharacterID + " : " + best_action_code + ".");
AI_Orders.SetOrderForCharacter(c.CharacterID, best_action_code, c.Position, Vector3.Normalize(player.Position - c.Position));
break;
case EActionCode.ActionCodeRoll:
Debug.Log("[AI] Set order for character " + c.CharacterID + " : " + best_action_code + ".");
float left_or_right = (UnityEngine.Random.value >= 0.5) ? 1.0f : -1.0f;
Vector3 direction_player = Vector3.Normalize(player.Position - c.Position);
Vector3 direction_roll = new Vector3(-direction_player.x, direction_player.y, direction_player.z) * left_or_right;
AI_Orders.SetOrderForCharacter(c.CharacterID, best_action_code, c.Position, direction_roll);
break;
case EActionCode.ActionCodeNoAction:
if (Vector3.Distance(player.Position, c.Position) < 100.0f)
{
Debug.Log("[AI] Set order for character " + c.CharacterID + " : " + best_action_code + " (stay in position).");
AI_Orders.SetOrderForCharacter(c.CharacterID, EActionCode.ActionCodeNoAction, c.Position, Vector3.Normalize(player.Position - c.Position));
}
else
{
Debug.Log("[AI] Set order for character " + c.CharacterID + " : " + best_action_code + " (move towards player).");
AI_Orders.SetOrderForCharacter(c.CharacterID, EActionCode.ActionCodeNoAction, player.Position, Vector3.Normalize(player.Position - c.Position));
}
break;
}
}
}
}
/// <summary>
/// Thinks the next player action.
/// </summary>
public void ThinkAnticipation()
{
Debug.Assert(this.Characters.ContainsKey(AI_Params.PlayerID), "[AI] Invalid player ID (" + AI_Params.PlayerID + ").");
AI_Character player = this.Characters[AI_Params.PlayerID];
bool changed = false;
// Training guard
if ((player.CurrentAction != null) && (player.CurrentAction.ActionCode == EActionCode.ActionCodeGuard))
{
this.TrainAnticipation(player, EActionCode.ActionCodeGuard);
}
// Training idle
if ((player.CurrentAction == null) || (player.CurrentAction.ActionCode == EActionCode.ActionCodeNoAction))
{
this.TrainAnticipation(player, EActionCode.ActionCodeNoAction);
}
// Decaying anticipation probability
if (this.LastUpdateTime > this.Anticipation_ActionTime)
{
this.Anticipation_Probability -= this.LastUpdateTime - this.Anticipation_ActionTime;
this.Anticipation_ActionTime = this.LastUpdateTime;
// Reset anticipation after a while
if (this.Anticipation_Probability < 0.0f)
{
this.Anticipation_Probability = 0.0f;
this.Anticipation_ActionCode = EActionCode.ActionCodeNoAction;
}
}
float[] outputs;
AI_DeepLearningNetwork network;
// Trying different anticipation timings
for (float t = 0.1f; t <= 1.0f; t += 0.1f)
{
// We will add the anticipation results from each AI for each action in this array
float[] actions = new float[(int)EActionCode.Count];
for (EActionCode code = EActionCode.ActionCodeNoAction; code < EActionCode.Count; code++)
{
actions[(int)code] = 0.0f;
}
// Each AI character participates in the anticipation
foreach (AI_Character c in this.Characters.Values)
{
if (c.CharacterType == ECharacterType.CharacterTypeEnemy && c.IsAlive)
{
// Anticipation from current/previous player action
if (player.CurrentAction != null)
{
network = this.Networks_Anticipation_1[player.CurrentAction.ActionCode];
outputs = network.Think(new float[] {
Vector3.Distance(c.PositionIn(t), player.PositionIn(t)),
Vector3.Angle(player.Direction, c.PositionIn(t) - player.PositionIn(t)),
Vector3.Angle(c.Direction, player.PositionIn(t) - c.PositionIn(t)),
t + this.LastUpdateTime - player.CurrentAction.CastTime
}, network.Variance);
for (EActionCode code = EActionCode.ActionCodeNoAction; code < EActionCode.Count; code++)
{
actions[(int)code] += outputs[(int)code];
}
}
else if (player.PreviousAction != null)
{
network = this.Networks_Anticipation_1[player.PreviousAction.ActionCode];
outputs = network.Think(new float[] {
Vector3.Distance(c.PositionIn(t), player.PositionIn(t)),
Vector3.Angle(player.Direction, c.PositionIn(t) - player.PositionIn(t)),
Vector3.Angle(c.Direction, player.PositionIn(t) - c.PositionIn(t)),
t + this.LastUpdateTime - player.PreviousAction.CastTime
}, network.Variance);
for (EActionCode code = EActionCode.ActionCodeNoAction; code < EActionCode.Count; code++)
{
actions[(int)code] += outputs[(int)code];
}
}
// Anticipation from current AI action
if (c.CurrentAction != null)
{
network = this.Networks_Anticipation_2[c.CurrentAction.ActionCode];
outputs = network.Think(new float[] {
Vector3.Distance(c.PositionIn(t), player.PositionIn(t)),
Vector3.Angle(player.Direction, c.PositionIn(t) - player.PositionIn(t)),
Vector3.Angle(c.Direction, player.PositionIn(t) - c.PositionIn(t)),
t + this.LastUpdateTime - c.CurrentAction.CastTime
}, network.Variance);
for (EActionCode code = EActionCode.ActionCodeNoAction; code < EActionCode.Count; code++)
{
actions[(int)code] += outputs[(int)code];
}
}
else
{
network = this.Networks_Anticipation_2[EActionCode.ActionCodeNoAction];
outputs = network.Think(new float[] {
Vector3.Distance(c.PositionIn(t), player.PositionIn(t)),
Vector3.Angle(player.Direction, c.PositionIn(t) - player.PositionIn(t)),
Vector3.Angle(c.Direction, player.PositionIn(t) - c.PositionIn(t)),
t
}, network.Variance);
for (EActionCode code = EActionCode.ActionCodeNoAction; code < EActionCode.Count; code++)
{
actions[(int)code] += outputs[(int)code];
}
}
}
}
// Choosing the most likely action
for (EActionCode code = EActionCode.ActionCodeNoAction; code < EActionCode.Count; code++)
{
if (this.Anticipation_Probability < actions[(int)code])
{
this.Anticipation_Probability = actions[(int)code];
this.Anticipation_ActionCode = code;
this.Anticipation_ActionTime = this.LastUpdateTime + t;
changed = true;
}
}
}
if (changed)
{
Debug.Log("[AI] Anticipating player action " + this.Anticipation_ActionCode + " in " + (this.Anticipation_ActionTime - this.LastUpdateTime) + "s.");
}
}
/// <summary>
/// Loads all neural networks.
/// </summary>
public void LoadNetworkState()
{
Debug.Log("[AI] Loading network state...");
// Loading network - action
this.Networks_Action = new Dictionary <EActionCode, AI_DeepLearningNetwork>();
for (EActionCode code = EActionCode.ActionCodeNoAction; code < EActionCode.Count; code++)
{
this.Networks_Action[code] = new AI_DeepLearningNetwork("AI_Action_" + code, new float[3, 2] {
{ 0.0f, 10000.0f }, // Input 1: Distance to player
{ -180.0f, +180.0f }, // Input 2: Angle to player from caster
{ -180.0f, +180.0f } // Input 3: Angle to caster from player
}, new float[1, 2] {
{ 0.0f, 1.0f } // Output 1: Probability of hitting
});
}
// Loading network - reaction
this.Networks_Reaction = new Dictionary <EActionCode, Dictionary <EActionCode, AI_DeepLearningNetwork> >();
for (EActionCode code1 = EActionCode.ActionCodeNoAction; code1 < EActionCode.Count; code1++)
{
this.Networks_Reaction[code1] = new Dictionary <EActionCode, AI_DeepLearningNetwork>();
for (EActionCode code2 = EActionCode.ActionCodeNoAction; code2 < EActionCode.Count; code2++)
{
this.Networks_Reaction[code1][code2] = new AI_DeepLearningNetwork("AI_Reaction_" + code1 + "_" + code2, new float[4, 2] {
{ 0.0f, 10000.0f }, // Input 1: Distance to player
{ -180.0f, +180.0f }, // Input 2: Angle to caster from player
{ -180.0f, +180.0f }, // Input 3: Angle to caster from player
{ -3.0f, +3.0f } // Input 4: Time advantage for player
}, new float[2, 2] {
{ -3.0f, +3.0f }, // Output 1: Average damage dealt
{ -3.0f, +3.0f } // Output 2: Average damage taken
});
}
}
// Loading network - reaction - roll direction
// Loading network - anticipation
float[,] outputs = new float[(int)EActionCode.Count, 2];
for (EActionCode code = EActionCode.ActionCodeNoAction; code < EActionCode.Count; code++)
{
outputs[(int)code, 0] = 0.0f;
outputs[(int)code, 1] = 1.0f;
}
this.Networks_Anticipation_1 = new Dictionary <EActionCode, AI_DeepLearningNetwork>();
this.Networks_Anticipation_2 = new Dictionary <EActionCode, AI_DeepLearningNetwork>();
for (EActionCode code = EActionCode.ActionCodeNoAction; code < EActionCode.Count; code++)
{
this.Networks_Anticipation_1[code] = new AI_DeepLearningNetwork("AI_Anticipation_2_" + code, new float[4, 2] {
{ 0.0f, 10000.0f }, // Input 1: Distance to player
{ -180.0f, +180.0f }, // Input 2: Angle to caster from player
{ -180.0f, +180.0f }, // Input 3: Angle to player from caster
{ -3.0f, +3.0f } // Input 4: Time since last action started
}, outputs); // Output 1: Probability of hitting
this.Networks_Anticipation_2[code] = new AI_DeepLearningNetwork("AI_Anticipation_1_" + code, new float[4, 2] {
{ 0.0f, 10000.0f }, // Input 1: Distance to player
{ -180.0f, +180.0f }, // Input 2: Angle to caster from player
{ -180.0f, +180.0f }, // Input 3: Angle to player from caster
{ -3.0f, +3.0f } // Input 4: Caster action advantage
}, outputs); // Output 1: Probability of hitting
}
Debug.Log("[AI] Loading network state - Done.");
}
public static AI_Order SetOrderForCharacter(int id, EActionCode code)
{
return(SetOrderForCharacter(id, code, Vector3.zero));
}
