斗地主AI算法——第十四章の主动出牌(3)
上一章已经排除了飞机、三带等牌型，那么除去炸弹王炸以外，我们只剩下单牌、对牌、三牌以及单顺、双顺、三顺了。
首先说单牌、对牌、三牌。其逻辑基本一样，只是出牌的个数有差别，即：如果该i牌数量满足这种牌型要求，即先打出，计算其剩余价值。
//出单牌
if (clsHandCardData.value_aHandCardList[i] > 0)
{
clsHandCardData.value_aHandCardList[i]--;
clsHandCardData.nHandCardCount--;
HandCardValue tmpHandCardValue = get_HandCardValue(clsHandCardData);
clsHandCardData.value_aHandCardList[i]++;
clsHandCardData.nHandCardCount++;
if ((BestHandCardValue.SumValue - (BestHandCardValue.NeedRound * 7)) <= (tmpHandCardValue.SumValue - (tmpHandCardValue.NeedRound * 7)))
{
BestHandCardValue = tmpHandCardValue;
BestCardGroup= get_GroupData(cgSINGLE, i, 1);
}
}
//出对牌
if (clsHandCardData.value_aHandCardList[i] > 1)
{
//尝试打出一对牌，估算剩余手牌价值
clsHandCardData.value_aHandCardList[i] -= 2;
clsHandCardData.nHandCardCount -= 2;
HandCardValue tmpHandCardValue = get_HandCardValue(clsHandCardData);
clsHandCardData.value_aHandCardList[i] += 2;
clsHandCardData.nHandCardCount += 2;
//选取总权值-轮次*7值最高的策略 因为我们认为剩余的手牌需要n次控手的机会才能出完，若轮次牌型很大（如炸弹） 则其-7的价值也会为正
if ((BestHandCardValue.SumValue - (BestHandCardValue.NeedRound * 7)) <= (tmpHandCardValue.SumValue - (tmpHandCardValue.NeedRound * 7)))
{
BestHandCardValue = tmpHandCardValue;
BestCardGroup = get_GroupData(cgDOUBLE, i, 2);
}
}
//出三牌
if (clsHandCardData.value_aHandCardList[i] > 2)
{
clsHandCardData.value_aHandCardList[i] -= 3;
clsHandCardData.nHandCardCount -= 3;
HandCardValue tmpHandCardValue = get_HandCardValue(clsHandCardData);
clsHandCardData.value_aHandCardList[i] += 3;
clsHandCardData.nHandCardCount += 3;
//选取总权值-轮次*7值最高的策略 因为我们认为剩余的手牌需要n次控手的机会才能出完，若轮次牌型很大（如炸弹） 则其-7的价值也会为正
if ((BestHandCardValue.SumValue - (BestHandCardValue.NeedRound * 7)) <= (tmpHandCardValue.SumValue - (tmpHandCardValue.NeedRound * 7)))
{
BestHandCardValue = tmpHandCardValue;
BestCardGroup = get_GroupData(cgTHREE, i, 3);
}
}
至于顺子的算法，和被动出牌的有一点点差别，就是因为没有了数量限制，所以需要遍历以i牌为起点可以组成的所有顺子。
//出单顺
if (clsHandCardData.value_aHandCardList[i] > 0)
{
int prov = 0;
for (int j = i; j < 15; j++)
{
if(clsHandCardData.value_aHandCardList[j]>0)
{
prov++;
}
else
{
break;
}
if (prov >= 5)
{
for (int k = i; k <= j; k++)
{
clsHandCardData.value_aHandCardList[k] --;
}
clsHandCardData.nHandCardCount -= prov;
HandCardValue tmpHandCardValue = get_HandCardValue(clsHandCardData);
for (int k = i; k <= j; k++)
{
clsHandCardData.value_aHandCardList[k] ++;
}
clsHandCardData.nHandCardCount += prov;
//选取总权值-轮次*7值最高的策略 因为我们认为剩余的手牌需要n次控手的机会才能出完，若轮次牌型很大（如炸弹） 则其-7的价值也会为正
if ((BestHandCardValue.SumValue - (BestHandCardValue.NeedRound * 7)) <= (tmpHandCardValue.SumValue - (tmpHandCardValue.NeedRound * 7)))
{
BestHandCardValue = tmpHandCardValue;
BestCardGroup = get_GroupData(cgSINGLE_LINE, j, prov);
}
}
}
}
//出双顺
if (clsHandCardData.value_aHandCardList[i] > 1)
{
int prov = 0;
for (int j = i; j < 15; j++)
{
if (clsHandCardData.value_aHandCardList[j]>1)
{
prov++;
}
else
{
break;
}
if (prov >= 3)
{
for (int k = i; k <= j; k++)
{
clsHandCardData.value_aHandCardList[k] -=2;
}
clsHandCardData.nHandCardCount -= prov*2;
HandCardValue tmpHandCardValue = get_HandCardValue(clsHandCardData);
for (int k = i; k <= j; k++)
{
clsHandCardData.value_aHandCardList[k] +=2;
}
clsHandCardData.nHandCardCount += prov*2;
//选取总权值-轮次*7值最高的策略 因为我们认为剩余的手牌需要n次控手的机会才能出完，若轮次牌型很大（如炸弹） 则其-7的价值也会为正
if ((BestHandCardValue.SumValue - (BestHandCardValue.NeedRound * 7)) <= (tmpHandCardValue.SumValue - (tmpHandCardValue.NeedRound * 7)))
{
BestHandCardValue = tmpHandCardValue;
BestCardGroup = get_GroupData(cgDOUBLE_LINE, j, prov*2);
}
}
}
}
//出三顺
if(clsHandCardData.value_aHandCardList[i] > 2)
{
int prov = 0;
for (int j = i; j < 15; j++)
{
if (clsHandCardData.value_aHandCardList[j]>2)
{
prov++;
}
else
{
break;
}
if (prov >= 2)
{
for (int k = i; k <= j; k++)
{
clsHandCardData.value_aHandCardList[k] -= 3;
}
clsHandCardData.nHandCardCount -= prov * 3;
HandCardValue tmpHandCardValue = get_HandCardValue(clsHandCardData);
for (int k = i; k <= j; k++)
{
clsHandCardData.value_aHandCardList[k] += 3;
}
clsHandCardData.nHandCardCount += prov * 3;
//选取总权值-轮次*7值最高的策略 因为我们认为剩余的手牌需要n次控手的机会才能出完，若轮次牌型很大（如炸弹） 则其-7的价值也会为正
if ((BestHandCardValue.SumValue - (BestHandCardValue.NeedRound * 7)) <= (tmpHandCardValue.SumValue - (tmpHandCardValue.NeedRound * 7)))
{
BestHandCardValue = tmpHandCardValue;
BestCardGroup = get_GroupData(cgTHREE_LINE, j, prov * 3);
}
}
}
}
因为本策略是必须解决掉至少一个i牌的，所以出牌操作放在循环内进行，也就是说，只要你不是炸3，若你手牌有3，在处理3时一定会return 就绝对不会再走到4。
if (BestCardGroup.cgType == cgERROR)
{
}
else if (BestCardGroup.cgType == cgSINGLE)
{
clsHandCardData.value_nPutCardList.push_back(BestCardGroup.nMaxCard);
clsHandCardData.uctPutCardType = BestCardGroup;
}
else if (BestCardGroup.cgType == cgDOUBLE)
{
clsHandCardData.value_nPutCardList.push_back(BestCardGroup.nMaxCard);
clsHandCardData.value_nPutCardList.push_back(BestCardGroup.nMaxCard);
clsHandCardData.uctPutCardType = BestCardGroup;
}
else if (BestCardGroup.cgType == cgTHREE)
{
clsHandCardData.value_nPutCardList.push_back(BestCardGroup.nMaxCard);
clsHandCardData.value_nPutCardList.push_back(BestCardGroup.nMaxCard);
clsHandCardData.value_nPutCardList.push_back(BestCardGroup.nMaxCard);
clsHandCardData.uctPutCardType = BestCardGroup;
}
else if (BestCardGroup.cgType == cgSINGLE_LINE)
{
for (int j = BestCardGroup.nMaxCard- BestCardGroup.nCount+1; j <= BestCardGroup.nMaxCard; j++)
{
clsHandCardData.value_nPutCardList.push_back(j);
}
clsHandCardData.uctPutCardType = BestCardGroup;
}
else if (BestCardGroup.cgType == cgDOUBLE_LINE)
{
for (int j = BestCardGroup.nMaxCard - (BestCardGroup.nCount/2) + 1; j <= BestCardGroup.nMaxCard; j++)
{
clsHandCardData.value_nPutCardList.push_back(j);
clsHandCardData.value_nPutCardList.push_back(j);
}
clsHandCardData.uctPutCardType = BestCardGroup;
}
else if (BestCardGroup.cgType == cgTHREE_LINE)
{
for (int j = BestCardGroup.nMaxCard - (BestCardGroup.nCount / 3) + 1; j <= BestCardGroup.nMaxCard; j++)
{
clsHandCardData.value_nPutCardList.push_back(j);
clsHandCardData.value_nPutCardList.push_back(j);
clsHandCardData.value_nPutCardList.push_back(j);
}
clsHandCardData.uctPutCardType = BestCardGroup;
}
else if (BestCardGroup.cgType == cgTHREE_TAKE_ONE)
{
clsHandCardData.value_nPutCardList.push_back(BestCardGroup.nMaxCard);
clsHandCardData.value_nPutCardList.push_back(BestCardGroup.nMaxCard);
clsHandCardData.value_nPutCardList.push_back(BestCardGroup.nMaxCard);
clsHandCardData.value_nPutCardList.push_back(tmp_1);
clsHandCardData.uctPutCardType = BestCardGroup;
}
else if (BestCardGroup.cgType == cgTHREE_TAKE_TWO)
{
clsHandCardData.value_nPutCardList.push_back(BestCardGroup.nMaxCard);
clsHandCardData.value_nPutCardList.push_back(BestCardGroup.nMaxCard);
clsHandCardData.value_nPutCardList.push_back(BestCardGroup.nMaxCard);
clsHandCardData.value_nPutCardList.push_back(tmp_1);
clsHandCardData.value_nPutCardList.push_back(tmp_1);
clsHandCardData.uctPutCardType = BestCardGroup;
}
else if (BestCardGroup.cgType == cgTHREE_TAKE_ONE_LINE)
{
for (int j = BestCardGroup.nMaxCard - (BestCardGroup.nCount / 4) + 1; j <= BestCardGroup.nMaxCard; j++)
{
clsHandCardData.value_nPutCardList.push_back(j);
clsHandCardData.value_nPutCardList.push_back(j);
clsHandCardData.value_nPutCardList.push_back(j);
}
if (BestCardGroup.nCount / 4 == 2)
{
clsHandCardData.value_nPutCardList.push_back(tmp_1);
clsHandCardData.value_nPutCardList.push_back(tmp_2);
}
if (BestCardGroup.nCount / 4 == 3)
{
clsHandCardData.value_nPutCardList.push_back(tmp_1);
clsHandCardData.value_nPutCardList.push_back(tmp_2);
clsHandCardData.value_nPutCardList.push_back(tmp_3);
}
if (BestCardGroup.nCount / 4 == 4)
{
clsHandCardData.value_nPutCardList.push_back(tmp_1);
clsHandCardData.value_nPutCardList.push_back(tmp_2);
clsHandCardData.value_nPutCardList.push_back(tmp_3);
clsHandCardData.value_nPutCardList.push_back(tmp_4);
}
clsHandCardData.uctPutCardType = BestCardGroup;
}
else if (BestCardGroup.cgType == cgTHREE_TAKE_TWO_LINE)
{
for (int j = BestCardGroup.nMaxCard - (BestCardGroup.nCount / 5) + 1; j <= BestCardGroup.nMaxCard; j++)
{
clsHandCardData.value_nPutCardList.push_back(j);
clsHandCardData.value_nPutCardList.push_back(j);
clsHandCardData.value_nPutCardList.push_back(j);
}
if (BestCardGroup.nCount / 5 == 2)
{
clsHandCardData.value_nPutCardList.push_back(tmp_1);
clsHandCardData.value_nPutCardList.push_back(tmp_1);
clsHandCardData.value_nPutCardList.push_back(tmp_2);
clsHandCardData.value_nPutCardList.push_back(tmp_2);
}
if (BestCardGroup.nCount / 5 == 3)
{
clsHandCardData.value_nPutCardList.push_back(tmp_1);
clsHandCardData.value_nPutCardList.push_back(tmp_1);
clsHandCardData.value_nPutCardList.push_back(tmp_2);
clsHandCardData.value_nPutCardList.push_back(tmp_2);
clsHandCardData.value_nPutCardList.push_back(tmp_3);
clsHandCardData.value_nPutCardList.push_back(tmp_3);
}
clsHandCardData.uctPutCardType = BestCardGroup;
}
return;
至此，主动出牌的所有逻辑均已实现，同时整个斗地主算法也基本完成了。接下来我们便可写一些测试模块来进行整合联调。
敬请关注下一章：斗地主AI算法——第十五章の测试模块
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