OutputAttack(float a, float d, float t, NNState nn, string dType)
{
_attack = a;
_defend = d;
_taunt = t;
_nn = nn;
_decideType = dType;
}
public static OutputAttack CalculateOutput(bool stunned, Fighter fighter)
{
float a = UnityEngine.Random.value;
float d = UnityEngine.Random.Range(0, 1 - a);
float t = 1 - (a + d);
float[] o = new float[0], hL = new float[0];
float[][] wHL = new float[0][], wO = new float[0][];
AI_Config conf = fighter.config;
StateData state = fighter.stateData;
float greedy = UnityEngine.Random.value;
NNState nn = new NNState();
string dType = null;
//
if (conf.usingAttackNN)
{
ConvertFightWeights(conf, state, out o, out hL, out wHL, out wO);
//Debug.Log($"FORW: {wHL.Length} * {wHL[0].Length} = {(wHL.Length * wHL[0].Length)}");
//Debug.Log($"FORW: {wO.Length} * {wO[0].Length} = {(wO.Length * wO[0].Length)}");
//Debug.Log($"\t\tFORW: {(wHL.Length * wHL[0].Length)} + {(wO.Length * wO[0].Length)} = {(wHL.Length * wHL[0].Length) + (wO.Length * wO[0].Length)}");
// calculate the hidden layer nodes output
for (int i = 0; i < hL.Length; i++)
{
hL[i] = AI.ReLu(AI.Σ(state.attState, wHL[i]) + 0);
}
// calculate the output nodes output
for (int i = 0; i < o.Length; i++)
{
o[i] = AI.Σ(hL, wO[i]);
}
// ship this.
nn = new NNState(o, hL, wO, wHL);
bool useNN = greedy < conf.showoff;
dType = useNN ? "nn" : "r";
//
if (useNN)
{
// squash & set the the final values for returning
a = AI.Sigmoid(o[0]);
d = AI.Sigmoid(o[1]);
t = AI.Sigmoid(o[2]);
//Debug.Log($"{fighter.name}: Combat Exploit");
}
else
{
//Debug.Log($"{fighter.name}: Combat Explore");
a = UnityEngine.Random.Range(0f, 1f);
d = UnityEngine.Random.Range(0f, 1f);
t = UnityEngine.Random.Range(0f, 1f);
}
}
else
{
//Debug.Log($"{fighter.name}: Combat Traditional");
a = UnityEngine.Random.Range(0, conf.attackTrad);
d = UnityEngine.Random.Range(0, conf.defendTrad);
t = UnityEngine.Random.Range(0, conf.tauntTrad);
}
// MOVE IS STUNNED FUNCT INTO HERE INSTEAD, PASS IN BOOL
if (stunned)
{
// check if defense is higher than taunt
if (d > t)
{
a = 0;
d = 1;
t = 0;
}
// else that means that taunt is higher than defense, & we can set taunt
else
{
a = 0;
d = 0;
t = 1;
}
return(new OutputAttack(a, d, t, nn, dType));
}
//
return(new OutputAttack(a, d, t, nn, dType));
}
public void Battle(int time, OutputAttack[] oA, Map map)
{
// SAVE ALL OF THESE FOR A COOL REPLAY FEATURE
//oA1.DEBUGSetVals(0, 1, 0);
//oA2.DEBUGSetVals(0, 1, 0);
// reset ran away after every battle
_ranAway = 0;
opp._ranAway = 0;
DisableAllRunIcons();
opp.DisableAllRunIcons();
int[][] r = Rewarder(map, oA[0].decision, oA[1].decision);
UpdateActions(oA[0].decision);
opp.UpdateActions(oA[1].decision);
//Debug.Log($"0: [{oA[0].decision}->{r[0][oA[0].decision]}][{r[0][0]},{r[0][1]},{r[0][2]}]\n1: [{oA[1].decision}->{r[1][oA[1].decision]}][{r[1][0]},{r[1][1]},{r[1][2]}]");
// compare & calculate
if (oA[0].decision == 0)
{
// ATTACK
if (oA[1].decision == 0)
{
// Both take damage
opp.TakeDmg(str);
TakeDmg(opp.str);
// how much i did to them - how much they did to me
//reward = new float[] { str - opp.str, opp.str - str };
//reward[0] = new float[] { str - opp.str, };
}
else if (oA[1].decision == 1)
{
//
int shieldStr = (int)Mathf.Floor(str / 3);
// oppponent takes a damage for every 3 str you have
opp.TakeDmg(shieldStr);
// take damage & is stunned
TakeDmg(1);
// You get stunned
Stun();
// how much i did to them - how much they did to me
//reward = new float[] { shieldStr - 2, 2 - shieldStr };
}
else if (oA[1].decision == 2)
{
int crit = str * 2;
// opponent takes damage x2
opp.TakeDmg(crit);
// how much i did to them - how much they did to me
//reward = new float[] { crit, -crit };
}
}
else if (oA[0].decision == 1)
{
// DEFEND
if (oA[1].decision == 0)
{
//
int oppShieldStr = (int)Mathf.Floor(opp.str / 3);
// you take a damage for every 3 str your opponent has
TakeDmg((int)Mathf.Floor(oppShieldStr));
// opponent takes damage
_opp.TakeDmg(1);
//
_opp.Stun();
// how much i did to them - how much they did to me
//reward = new float[] { 2 - oppShieldStr, oppShieldStr - 2 };
}
else if (oA[1].decision == 1)
{
// take one step away from each other
//
Vector2Int s1 = v2Int;
Vector2Int s2 = _opp.v2Int;
//
StepBackwardsFrom(time, map, s2);
_opp.StepBackwardsFrom(time, map, s1);
// how much i did to them - how much they did to me
//reward = new float[] { 0, 0 };
}
else if (oA[1].decision == 2)
{
// opponent powers up
_opp.PowerUp();
// how much i did to them - how much they did to me
//reward = new float[] { 3 - 0, 0 - 3 };
}
}
else if (oA[0].decision == 2)
{
// TAUNT
if (oA[1].decision == 0)
{
//
int oppCrit = _opp.str * 2;
// you take damage x2
TakeDmg(oppCrit);
// how much i did to them - how much they did to me
//reward = new float[] { -oppCrit, oppCrit };
}
else if (oA[1].decision == 1)
{
// you power up
PowerUp();
// how much i did to them - how much they did to me
//reward = new float[] { 3 - 0, 0 - 3 };
}
else if (oA[1].decision == 2)
{
// both powers down
PowerDown();
_opp.PowerDown();
// how much i did to them - how much they did to me
//reward = new float[] { strIsMin ? 0 : -1, opp.strIsMin ? 0 : -1 };
}
}
//
if (!config.isHuman && config.usingAttackNN)
{
int z = 0;
NNState nn = oA[z].nn;
float[] state = stateData.attState;
float[] error = new float[nn.O_out.Length];
float[] fin = new float[nn.O_out.Length]; // assign this
float[] derivF = new float[nn.O_out.Length];
float[] derivO = new float[nn.O_out.Length];
float[] derivH = new float[nn.H_out.Length];
float[][] D_out = new float[nn.O_out.Length][];
float[][] D_hidden = new float[nn.H_out.Length][];
//
for (int i = 0; i < nn.W_hidden.Length; i++)
{
D_hidden[i] = new float[state.Length];
}
//
for (int i = 0; i < fin.Length; i++)
{
//
fin[i] = AI.Sigmoid(nn.O_out[i]);
//
D_out[i] = new float[nn.H_out.Length];
}
float[][] newWH = new float[0][];
float[][] newWO = new float[0][];
//Debug.Log($"BACK: {nn.W_hidden.Length}*{nn.W_hidden[0].Length} = {nn.W_hidden.Length * nn.W_hidden[0].Length}");
//Debug.Log($"BACK: {nn.W_out.Length}*{nn.W_out[0].Length} = {nn.W_out.Length * nn.W_out[0].Length}");
//Debug.Log($"\t\tBACK: {nn.W_hidden.Length * nn.W_hidden[0].Length} + {nn.W_out.Length * nn.W_out[0].Length} = {(nn.W_hidden.Length * nn.W_hidden[0].Length) + (nn.W_out.Length * nn.W_out[0].Length)}");
// BackProp
for (int i = 0; i < r[z].Length; i++) //3
{
// back prop
error[i] = GM.lR * Mathf.Pow(r[z][i] * fin[i], 2);
derivF[i] = 2 * (GM.lR * Mathf.Pow(r[z][i], 2)) * fin[i];
//
derivO[i] = AI.Sigmoid(nn.O_out[i], true) * derivF[i];
//
for (int j = 0; j < D_out[i].Length; j++) //12
{
D_out[i][j] = nn.H_out[j] * derivO[i];
derivH[j] = nn.W_out[i][j] * derivO[i];
//
for (int k = 0; k < D_hidden[j].Length; k++) //20
{
D_hidden[j][k] = state[k] * derivH[j];
newWH = nn.W_hidden;
newWH[j][k] += D_hidden[j][k] * Mathf.Sign(r[z][i]);
}
newWO = nn.W_out;
newWO[i][j] += D_out[i][j] * Mathf.Sign(r[z][i]);
}
}
//
//for (int i = 0; i < derivF.Length; i++)
//{
// Debug.Log(derivF[i]);
//}
// if we have toggled off their ablility to learn
if (GM.nnIsLearning[z])
{
config.UpdateAttack(newWH, newWO);
}
}
if (!opp.config.isHuman && opp.config.usingAttackNN)
{
int z = 1;
NNState nn = oA[z].nn;
float[] state = opp.stateData.attState;
float[] error = new float[nn.O_out.Length];
float[] fin = new float[nn.O_out.Length]; // assign this
float[] derivF = new float[nn.O_out.Length];
float[] derivO = new float[nn.O_out.Length];
float[] derivH = new float[nn.H_out.Length];
float[][] D_out = new float[nn.O_out.Length][];
float[][] D_hidden = new float[nn.H_out.Length][];
//Debug.Log($"oOut: {nn.O_out.Length}, hOut: {nn.H_out.Length}, wOut: [{nn.W_out.Length}][{nn.W_out[0].Length}], wHidden: [{nn.W_hidden.Length}][{nn.W_hidden[0].Length}]");
//
for (int i = 0; i < nn.W_hidden.Length; i++)
{
D_hidden[i] = new float[state.Length];
}
//
for (int i = 0; i < fin.Length; i++)
{
//
fin[i] = AI.Sigmoid(nn.O_out[i]);
//
D_out[i] = new float[nn.H_out.Length];
}
float[][] newWH = new float[0][];
float[][] newWO = new float[0][];
// BackProp
for (int i = 0; i < r[z].Length; i++) //3
{
// back prop
error[i] = GM.lR * Mathf.Pow(r[z][i] * fin[i], 2);
derivF[i] = 2 * (GM.lR * Mathf.Pow(r[z][i], 2)) * fin[i];
//
derivO[i] = AI.Sigmoid(nn.O_out[i], true) * derivF[i];
//
for (int j = 0; j < D_out[i].Length; j++) //12
{
D_out[i][j] = nn.H_out[j] * derivO[i];
derivH[j] = nn.W_out[i][j] * derivO[i];
//
for (int k = 0; k < D_hidden[j].Length; k++) //20
{
D_hidden[j][k] = state[k] * derivH[j];
newWH = nn.W_hidden;
newWH[j][k] += D_hidden[j][k] * Mathf.Sign(r[z][i]);
}
newWO = nn.W_out;
newWO[i][j] += D_out[i][j] * Mathf.Sign(r[z][i]);
}
}
// if we haven't toggled off their ablility to learn
if (GM.nnIsLearning[z])
{
opp.config.UpdateAttack(newWH, newWO);
}
}
for (int i = 0; i < 2; i++)
{
int currentReward = r[i][oA[i].decision];
map.fC.UpdateGraph(i, currentReward);
GM.battleAvgThisMatch[i].Add(currentReward);
}
//
//using (StreamWriter sW = File.AppendText("masterLog.tsv"))
//{
// for (int i = 0; i < 2; i++)
// {
// sW.WriteLine($"{sD[i]}\t{oA[i].decision}\t{r[i][0]},{r[i][1]},{r[i][2]}");
// }
//}
}
