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Typically for a pure data change like this, we would not use separate classes. Instead, you could make your class non-abstract (say "BasicMob" to leave room if you need more complex mob classes in future) and give it one or several Factory Methods that populate the data of your mob to make a specific variant. eg.. public static BasicMob CreateFireElemental(...


TL;DR If you use expected values you would not need to use chances explicitly although you would calculate a risk neutral entity. Your could as you mentioned go for a ML approach here, but you might as well assign each adjacent field its expected value if rolling a set of dice, i.e. its chance [since you get 1 per roll] and maximize over the sum of chances....


There are a small fixed set of possible locations on the board so measuring each one against your metrics and picking the best one would be no problem. The issue is, whether you can come up with good, (or merely good enough,) metrics. In other words, if you want the best place(s) to place a settlement then you need to define what best means. Then the rest ...


Your main game loop should usually loop through 3 main processes. Each of these processes usually run in context to a specific scene/screen in your game .. menu screen, gameplay screen, exit screen , etc. Process input: this is usually where people use an observer design pattern and create an event dispatcher which dispatches events to game objects who are ...


You can use my script for converting 3d 3dsmax animations to spritesheets Link:


Use a maze generation algorithm Use a modified form of Prim's Algorithm to create a basic maze of 20 rooms or so. Choose two rooms to be start and end rooms, ensuring the end is always reachable. Block off random doors with different door types and randomly add doors where two adjacent rooms are not connected (with low probability)

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