Finite State Machines Computer theory covers several types of abstract machines, - PowerPoint Presentation

Slide1

Finite State Machines

Computer theory covers several types of abstract machines,

including Finite State Machines.Slide2

Finite State MACHINES

Also known as Finite State Automata

Also known as FSM, or State

MachinesSlide3

Facts about FSM, in general terms

Finite State Machines are important

part of intelligent

systems.

The most

famous FSM

is

the

Turing Machine, which can represent the logic of

almost any

computer algorithm.

FSMs exist

in everything from elevators to traffic lights; from vending machines to combination locks; from credit card number validation to complex artificial intelligence systems. Slide4

Main FSM Categories

Acceptors

Transducers

SequencersSlide5

Acceptors

Acceptor machines are useful in creating simple grammars. If

it is possible to build

an FSM to represent a

grammar,

it is called a regular language.

A single acceptor statement in a regular language is called a regular expression.

Example:

When

you learn a new programming

language for the first time, you see a sub-language

that

has syntax rules

. Regular

expressions

are used to

define the

syntax.Slide6

Transducers

Transducers read input files

and generate a corresponding output file.

These tools are used to consolidate multiple files

into a single large data

file.

Example:

Transducers

convert

from generic data into a game's final memory

format for faster loading time.Slide7

Sequencers

Sequencer

are FSMs are used to

control a sequence of events or actions.

Example Sequencers can be

used to model game behavior

.Slide8

Sequencers store two types of information

A set of states that represent the scenarios

of the game. These are the configurations that the AI will be

immersed in

.

A set of transitions that are conditions that

move a behavior from one scenario to another. These scenarios are described as the transition between two

states in a directed

way.

FSM sequencers depict

a complete network or collection of possible actions (the states) and ways to change from one action to the other.Slide9

Examine a basic Virtual pet

A pet

isHUNGRY

.

If you provide it with food, the pet

isEATING

that food, it will not be hungry anymore.

After eating (consuming energy calories), the pet

isPLAYING

.

Pet

isHUNGRY

again after burning calories all the consumed calories during play

.

Three states are described:

isHUNGRY

,

isEATING

,

isPLAYING

.

Statements that describe how and when the states are altered are called transitions.Slide10

Transitions

Assume the

pet begins in a

isHUNGRY

state.

If the user supplies food, the pet is in the state of

isEATING

.

If food

is consumed and the stomach is full, the

pet will transition into the

isPLAYING

state.

A pet

is always in one of a finite number of

states.

A Transition is

based on two things: the current state, and actions and conditions. Slide11

FSM:

virtual pet

Note:

A

dead pet cannot be revived.

Slide12

Implementation

Use a switch statement.

Each

of the cases in the switch controls a specific state and evaluates the possibility of changing states due to a specific transition in the automata being selected.

Each

state's activities can be divided into specific areas:

The name of the state

The default actions to be carried out in that state

The calculations to perform in order to evaluate outgoing transitionsSlide13

const

isHUNGRY:int = 1

;

const

isEATING:int = 2

;

var

state:int

;

switch

(state) {

case

isHUNGRY:

// default actions to be carried out when the pet is hungry

break;

case

isEATING:

//

default actions to be carried out when the pet is eating

break

;

.

.

.

}