1. Finite State Machine for Games
Mohammad Zikky, M.T
Ref: Chenney, CS679 lectures
AI Game Programming Wisdom 2

2. Outline AI and Game Introduction/examples Design Implementation
Intuition
State-based
Implementation
Extending
Stack-based
Fuzzy-state machine

3. What is AI? (and is NOT)
AI is the control of non-human entities in a game
The other cars in a car game
The opponents and monsters in a shooter
Your units, your enemy’s units and your enemy in a RTS game
But, typically does not refer to passive things that just react to the player and never initiate action
That’s physics or game logic
For example, the blocks in Tetris are not AI, nor is a flag blowing in the wind

4. AI in the Game Loop
AI is updated as part of the game loop, after user input, and before rendering

5. AI Update Step The sensing phase determines the state of the world
May be very simple - state changes all come by messaging
Or complex - figure out what is visible, where your team is, etc
The thinking phase decides what to do given the world
The core of AI
The acting phase tells the animation what to do
AI Module
Sensing
Game Engine
Thinking
Acting
Fall 2012

6. AI by Polling Senses: then acts on it
AI gets called at a fixed rate
AI by Polling
Senses:
looks to see what has been changed in the world
then acts on it
Generally inefficient and complicated
Different characters might require different polling rate

7. Event Driven AI Events triggered by a message Example messages:
does everything in response to events in the world
Event Driven AI
Events triggered by a message
basically, a function gets called when a message arrives, just like a user interface)
Example messages:
You have heard a sound
Someone has entered your field of view
A certain amount of time has passed, so update yourself
Fall 2012

8. AI Techniques in Games
Basic problem: Given the state of the world, what should I do?
A wide range of solutions in games:
Finite state machines, Decision trees, Rule based systems, Neural networks, Fuzzy logic
A wider range of solutions in the academic world:
Complex planning systems, logic programming, genetic algorithms, Bayes-nets
Typically, too slow for games

9. Expressiveness
What behaviors can easily be defined, or defined at all?
Propositional logic:
Statements about specific objects in the world – no variables
Jim is in room7, Jim has the rocket launcher, the rocket launcher does splash damage
Go to room8 if you are in room7 through door14
Predicate Logic:
Allows general statement – using variables
All rooms have doors
All splash damage weapons can be used around corners
All rocket launchers do splash damage
Go to a room connected to the current room
Fall 2012

10. Finite State Machines (FSMs)
A set of states that the agent can be in
Connected by transitions that are triggered by a change in the world
Normally represented as a directed graph, with the edges labeled with the transition event
Ubiquitous in computer game AI
Fall 2012

11. Formal Definitions (N. Philips)
"An abstract machine consisting of a set of states (including the initial state), a set of input events, a set of output events, and a state transition function.
The function takes the current state and an input event and returns the new set of output events and the next state. Some states may be designated as "terminal states".
The state machine can also be viewed as a function which maps an ordered sequence of input events into a corresponding sequence of (sets of) output events.
Finite State Automaton: the machine with no output
Fall 2012

12. FSM with Output: vending machines
OJ & AJ for 30 cents
State table

13. Vending Machine: state diagram

14. FSM and Game
Game character behavior can be modeled (in most cases) as a sequence of different “mental state”, where change is driven by the actions of player/other characters, …
Natural choice for defining AI in games

15. FSM Examples
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19. PacMan State Machine PacMan eats a Power Pill Timer <= 0
Collision with GhostBox
Collision with PacMan

20. Actions of States Roam; Timer--; If PacMan gets close, PathTo (PacMan)
PathAwayFrom (PacMan)
Timer—
Move back-and-forth
PathTo (GhostBox)

21. Ex: predator vs. prey Prey (laalaa) Sees predator No more threat Flee
Idle
(stand,wave,…)
Sees predator
No more threat
Flee
(run)
Dead
captured

22. Predator (Raptor) Tidle > 5 Tdining>5 Dining Prey captured
(stand)
Tidle > 5
Tdining>5
Hungry
(wander)
Dining
Prey captured
Prey in sight
Pursuit
(run)
Tpursuit > 10
Fall 2012

23. Idling LaaLaa This page illustrates: hierarchical state,
Non-deterministic state transition
Target arrived
Wander
(set random target)
20%
Stand
Tstand>4 R
30%
Wave
50%
Twave>2

24. FSM Design

25. Quake2 Examples Intuitive thinking: model the events and state changes
Quake2 uses 9 different states:
standing, walking, running, dodging, attacking, melee, seeing the enemy, idle and searching.
Incomplete design

26. Quake: Rocket
Fall 2012

27. Shambler monster
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28. FSM Advantages Very fast – one array access
Expressive enough for simple behaviors or characters that are intended to be “dumb”
Can be compiled into compact data structure
Dynamic memory: current state
Static memory: state diagram – array implementation
Can create tools so non-programmer can build behavior
Non-deterministic FSM can make behavior unpredictable
Fall 2012

29. FSM Disadvantages Number of states can grow very fast
Exponentially with number of events: s=2e
Number of arcs can grow even faster: a=s2
Propositional representation
Difficult to put in “pick up the better powerup”, “attack the closest enemy”
Expensive to count: Wait until the third time I see enemy, then attack
Need extra events: First time seen, second time seen, and extra states to take care of counting
Fall 2012

30. FSM Control System Implementation

31. FSM Implementation
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32. Previous Example
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33. Code 1
Ad hoc implementation
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34. Code 1p
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35. Code 2
Structure, Readable, maintainable
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36. Hierarchical …
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37. FSM Extensions

38. Advanced Issues Hierarchical FSM Non-deterministic FSM Swapping FSM
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39. Hierarchical FSMs What if there is no simple action for a state?
Expand a state into its own FSM, which explains what to do if in that state
Some events move you around the same level in the hierarchy, some move you up a level
When entering a state, have to choose a state for its child in the hierarchy
Set a default, and always go to that
Or, random choice
Depends on the nature of the behavior
Fall 2012

40. Stack-based FSM Pushdown automaton (PDA)
History stack: Remember previous state; create characters with a memory …
Fall 2012

41. Goal-based vs. State-based
There is also a slight derivative to the state-based engine, but it used in more complicated games like flight simulators and games like MechWarrior. They use goal -based engines - each entity within the game is assigned a certain goal, be it 'protect base', 'attack bridge', 'fly in circles'. As the game world changes, so do the goals of the various entities.
Fall 2012

42. Processing Models Polling Event-driven FSM update frequency
Easy to implement and debug
Inefficiency (Little Red example)
Event-driven
Publish-subscribe messaging system
Game engine sends event messages to individual FSMs
An FSM subscribes only to the events that have the potential to change the current state
Higher efficiency, non-trivial implementation
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43. Efficiency and Optimization
In AI, FSM is the most efficient technology available
Yet, there is always room for improvement
Level of Detail: depending on the condition (e.g., distance with player), use different FSM, or different update frequency
Fall 2012

44. An Example FSM in Football Game

45. Class : Sepakbola Lapangan
Jadwal Pertandingan (Liga, Tournament, 2x45 mnt)
Skuad Pemain (11 di lapangan + cadangan)
Taktik & Strategi (4-4-2 Menyerang / Bertahan)
Latihan
Staff Pemain (Pelatih , Ass Pelatih, Dokter)
Keuangan
Transfer Pemain

46. Object : Pemain Bola Technicals Intellegents Physicals Temperaments
Cetak Gol, Giring Bola, Tangkap Bola (penjaga Gawang), Control Bola, Tackling Bola, Tendang Jarak Jauh, Marking, dll

47. FSM Secara Global dlm S.Bola

48. Class : Sepakbola Keterangan CG : Cetak Gol
MM : Menjaga Lawan (Man Marking)
TB : Tangkap Bola (Penjaga Gawang)
MZ : Menjaga Daerah (Zona Marking)
US : Umpan Silang
SB : Sundul Bola
UP : Umpan Pendek
GB : Giring Bola
UL : Umpan Lambung
TJ : Tendangan Jarak Jauh
LMD : Lari Maju ke depan
TC : Tendangan Pojok
LMBC : Lari Mundur ke Belakang
AM : Mental Menyerang
TP : Tendangan Pinalti
DM : Mental Bertahan
T : Tackling / Jegal
LMB : Lari Kejar Bola
LB : Lempar Bola

49. Object : Penjaga Gawang
Tangkap
~M, K
~M, K
Umpan Lambung
Umpan Pendek
~M, K
M, K
M, K
~M,K
Tendangan Gawang
Mental Bertahan
Dekati Bola

50. Object : Penjaga Gawang
M = Musuh Mendekat
~M = Musuh Menjauh
K = Teman Mendekat
~K = Teman Menjauh

51. Object : Pemain Bertahan (Tengah)
Umpan Lambung
M,~M,K,~K
Umpan Pendek
Tackling : Keras M
Jemput Bola
Dapat Bola
Marking=Zona
Mental : Bertahan M

52. Object : Pemain Bertahan (SAYAP)
Umpan Lambung
Takling : Normal
Menggiring Bola Maju
Jemput Bola
Dapat Bola
Umpan Pendek
Mental : Normal

53. Object : Gelandang Bertahan
Umpan Lambung
Takling : Normal
Menggiring Bola Maju
Tendangan Jrk Jauh
Jemput Bola
Dapat Bola
Umpan Pendek

54. Object : Gelandang Serang
Umpan Lambung
Takling : Ringan
Menggiring Bola Maju
Tendangan Jrk Jauh
Jemput Bola
Dapat Bola
Umpan Pendek

55. Object : Sayap Kanan / Kiri
Umpan Silang
Umpan Lambung
Umpan Pendek
Dapat Bola
Jemput Bola
Menggiring Bola Maju
Tackling : Ringan

56. Object : Penyerang (Striker)
Giring Bola
Umpan Pendek
Umpan Silang
Cetak GOL
Tendangan Jrk Jauh
Jemput Bola
Dapat Bola

57. References Web references: Game Programming Gems Sections 3.0 & 3.1
csr.uvic.ca/~mmania/machines/intro.htm
Game Programming Gems Sections 3.0 & 3.1
It’s very very detailed, but also some cute programming
Fall 2012