我赞成每场比赛多打几场比赛。制作50款游戏只是抛硬币。我需要做1000个游戏，才能在测试算法之间找到合理的区别。

下载无畏1.2。

策略:

keep track of all possible positions for ships that have >0 hits. The list never gets bigger than ~30K so it can be kept exactly, unlike the list of all possible positions for all ships (which is very large). The GetShot algorithm has two parts, one which generates random shots and the other which tries to finish sinking an already hit ship. We do random shots if there is a possible position (from the list above) in which all hit ships are sunk. Otherwise, we try to finish sinking a ship by picking a location to shoot at which eliminates the most possible positions (weighted). For random shots, compute best location to shoot based on the likelihood of one of the unsunk ships overlapping the location. adaptive algorithm which places ships in locations where the opponent is statistically less likely to shoot. adaptive algorithm which prefers to shoot at locations where the opponent is statistically more likely to place his ships. place ships mostly not touching each other.

我预测，能够逆向设计对手随机种子和呼叫模式的人将获胜。

但不确定这种可能性有多大。

当然，我们也有可能在游戏的基础上运行一系列类似的游戏。

添加3d飞机或能够移动一艘船而不是射击回合等内容可能会改变游戏。

如果你强迫自己进行分析，那么你可能会发现随机对手的机制非常低效。它允许自己重新选择已经目标的位置，并让框架强制它重复，直到它击中它还没有触及的位置，或者每次移动的时间限制到期。

这个对手有类似的行为(有效的位置分布是相同的)，它只是自己进行完整性检查，每次调用只消耗一个随机数生成(平摊)。

这使用了我的扩展/库答案中的类，我只提供关键方法/状态。

Shuffle源自Jon Skeet的回答

class WellBehavedRandomOpponent : IBattleShipOpponent
{
    Rand rand = new Rand();
    List<Point> guesses;
    int nextGuess = 0;

    public void PlaceShips(IEnumerable<Ship> ships)
    {
        BoardView<bool> board = new BoardView<bool>(BoardSize);
        var AllOrientations = new[] {
            ShipOrientation.Horizontal,
            ShipOrientation.Vertical };

        foreach (var ship in ships)
        {
            while (!ship.IsPlaced)
            {
                var l = rand.Pick(board.Select(c => c.Location));
                var o = rand.Pick(AllOrientations);
                if (ship.IsLegal(ships, BoardSize, l, o))
                    ship.Place(l, o);
            }
        }
    }

    public void NewGame(Size size, TimeSpan timeSpan)
    {
        var board = new BoardView<bool>(size);
        this.guesses = new List<Point>(
            board.Select(x => x.Location).Shuffle(rand));
        nextGuess = 0;
    }

    public System.Drawing.Point GetShot()
    {
        return guesses[nextGuess++];
    }

    // empty methods left out 
}

我现在没有时间写一个完整的算法，但我有一个想法:如果你的对手随机放置船只，放置概率不会是一个以(5.5,5.5)为中心的简单分布吗?例如，战列舰(5个单位长)在x维度的放置可能性如下:

x    1 2 3 4 5  6  7 8 9 10
P(x) 2 4 6 8 10 10 8 6 4 2

同样的计算也适用于y。其他船只的分布不会那么陡峭，但你最好的猜测仍然是中心。在此之后，数学方法将慢慢地向中心外辐射对角线(可能是平均船的长度，17/5)。例:

...........
....x.x....
.....x.....
....x.x....
...........

显然，这个想法需要添加一些随机性，但我认为从纯粹的数学角度来看，这是可行的。

我赞成每场比赛多打几场比赛。制作50款游戏只是抛硬币。我需要做1000个游戏，才能在测试算法之间找到合理的区别。

下载无畏1.2。

策略:

keep track of all possible positions for ships that have >0 hits. The list never gets bigger than ~30K so it can be kept exactly, unlike the list of all possible positions for all ships (which is very large). The GetShot algorithm has two parts, one which generates random shots and the other which tries to finish sinking an already hit ship. We do random shots if there is a possible position (from the list above) in which all hit ships are sunk. Otherwise, we try to finish sinking a ship by picking a location to shoot at which eliminates the most possible positions (weighted). For random shots, compute best location to shoot based on the likelihood of one of the unsunk ships overlapping the location. adaptive algorithm which places ships in locations where the opponent is statistically less likely to shoot. adaptive algorithm which prefers to shoot at locations where the opponent is statistically more likely to place his ships. place ships mostly not touching each other.