CHAPTER 10: CORE MECHANICS
Definitions and Mechanisms
Core Mechanics The rules of the game How the player interacts with the rules Monopoly example:
Game ships with 3 pages of rules, but that would not actually be enough because you need: The prices of property Community and chance cards Rent collected from each property Layout of the board
Define rules by data and algorithms Eventually the CMs should be so well documented that programmers
could grab the documentation and have everything they need. Interesting fact: The CMs and the game engine relationship is very
close, because the CMs specify how the game engine behaves.
Functions of Core Mechanics Operate the internal economy of the game Present active challenges Accept player actions & transmit triggers to
the storytelling engine Detect victory or loss Operate the ai Switch the game from mode to mode
Real Time vs Turn Based Games CMs work different ways for both
Turn Based Games: Wait for the player to do something then calculate the result and effects with CMs. There might be computations going on in between turns, but the AI opponents will still do moves based on the mechanics.
Real Time: Core mechanics are always implementing even if the player does nothing. AI will walk around, simulations will continue.
CMs and Level Design When a game loads a level, each level has
its own game type, winning conditions, timing, and sequence of challenges that appear. CMs specify how the different challenges actually work but not what levels they will appear in. Basically the CMs provide the level designers building blocks.
Important Core Mechanics Concepts Resources Entities Attributes Mechanics Numeric and Symbolic Relationships
The Internal Economy Sources Drains Converters Traders Production Mechanisms Tangible and Intangible Resources Feedback Loops, Mutual Dependencies, and Deadlocks Static and Dynamic Equilibrium
Core Mechanics and Gameplay So far we have described the core
mechanics as a system but we need to emphasize a little more on the role of the player. As we discussed the core mechanics allow challenges to be detected and completed.
Core Mechanics and Gameplay Passive Challenges Active Challenges Player Actions Trigger Mechanics Actions Accompanied By Data
Core Mechanics Design Goals of Core Mechanics Design
Strive for simplicity and elegance Simple rules are the easiest for new players to understand, and
gives a much wider appeal Look for patterns, then generalize
Recognize patterns instead of documenting dozens of individual cases
Suppose you decide that swamp leeches really belong in water and that a swamp leech should lose 10 points of health for every minute that it’s out of the water. Later, you decide that a salamander should lose 5 points of health for every minute that it’s out of fire. Instead of coming up for a mechanic for each creature explain a general case only once for all environmental creatures
Core Mechanics Design Don’t try to get everything on paper
If you try to get everything on paper you will never finish It is more important to be clear and precise in your
documentation Find the right level of detail
Not enough details, programmers might assume thing and programming mistakes and errors will show up. But this will allow the programming stage to be fast
To much detail could take too long Revisit your earlier design work
Core Mechanics Design Things to look out for:
What is the player going to do? Your flowboard of the game’s structure Your list of gameplay modes and your plans for them The general outline of the story you want to tell The names of any characters Your general plans for each level in the game The progression of the levels Any victory or loss conditions Any non-gameplay actions
Core Mechanics Design List your entities and resources Add the mechanics:
Think about your resources Study your entities Analyze challenges and actions Look for global mechanic
Random Numbers and the Gaussian Curve Pseudo - Random Numbers
Random number generator algorithms take in something called a seed. Then the algorithm creates a random number. The only issue is that if you don’t change the seed you will end up with the same random number. Not really fun, especially for some kind of game that includes a dice roll, but it is pretty good for testing.
Random Numbers and the Gaussian Curve
Monte Carlo Simulations Sometimes it is hard to test a system when
there are many different inputs that could occur. So we do something called a Monte Carlo simulation, this just means that we test a system with a bunch of inputs and record the outputs in a file.
Random Numbers and the Gaussian Curve Uniform Distributions
The chance of getting one number is equal to the chance of any other number. Like a dice roll.
Nonuniform Distribution Different probability for each randomly generated number.
Like 2 die being rolled, chance of rolling a 12 is different then rolling a 6
Gaussian Curve Appears very often in nature, it is just like a 2 die being rolled.
