FINITE STATE MACHINES AI Game Engine Programming
Finite State Machines (FSM)
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FSM is a data structure used in AI contexts
Contents of state machine: machine states, several input conditions and transaction function
How transaction checking made in classic (271)
Most game FSM are coded using Moore model (272)
o Where you put your actions inside the state instead of the transaction between states (Sit/ Stand Up
Example)
o Moore Model = Mealy Machine Model
PAC-MAN FSM Example:
FSM Skeletal Code:
o FSMState class: the basic state in the system
o FSMMachine class: houses all states and acts as state machine
o FSMAIControl class: houses state machine and game specific code (such as perception data)
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FINITE STATE MACHINES AI Game Engine Programming
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The FSMState class:
o Each state should have following functions:
 Enter(): this function is always run when you enter the state to do initializations
 Exit(): run when leaving state to cleanup and run any code after leaving (Mealy State)
 Update(): This is the main function that is called every AI processing call (Moore)
 Init(): Resets the state
 CheckTransition(): This function should return the enumeration value to next state to run
FSM Pros:
o Easy to implement, debug and make code centralized
FSM Cons:
o State oscillation
Extensions to FSM:
o Hierarchical FSMs:
 FS that contains another FS and called “super state”
o Message and Event-Based FSMs:
 Using events to triggers rather than polling model
o FSMs with Fuzzy Transitions:
 Adding more calculations or simple comparisons to the transition states
 Most of the transition computations are done in the state itself rather than Control class
o Stack-Based FSMs:
 Use stack rather than current state so that you can make interpretations to the system and
come back again to the previous state when interpretation done (Attack/Take Cover
Example)
o Multiple Concurrent FSMs:
 multiple FSMs between multiple characters
 multiple FSMs for same character
 This issue in handled by a manager (could be General FSM) that coordinates between FSMs
 RTS Game Example: AI opponent could need separate decision state machines for resources
management, research and combat and so on. These FSMs might communicate throw an
observer of some kind (could be a FSM that uses output of these FSMs as transition
conditions)
 Drawbacks of this issue: oscillations and data overwriting
o Data-Driven FSM:
 Motivation: adding new AI by nonprogrammers
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FINITE STATE MACHINES AI Game Engine Programming
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Techniques to do this:
 Scripted FSMs: easy for programmers hard for designers
 Visual Editor: easy for designers hard for programmers
o Inertial FSM:
 If a state has been actuated, it stays actuated for some time, or that new states have to
overcome some inertia before they can fire in the first place. This can be done in the states
themselves or on the perceptions that fire the states
Optimizations to FSM:
o Load Balancing Both FSM and Perceptions
 Refers to spreading the amount of computation to be done over time to lessen the
immediate load on the processor. This is done by:
 Make system run at a set of scheduled rate (every 2 seconds)
 Have system that give better results by having more time
o Level of Detail (LOD) AI Systems:
 Ignoring some AI details when they are not needed
 Teleport example (Start 304)
o Shared Data Structures:
 If there is a computation that is done my many states then, this computation could be
computed by one state and then be send to the sheared control so any other state can take
the results without re-computing it
 Blackboard paradigm (End 304)
You can separate the state-based portion of your code from the AI code
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