Brian Mac Namee

„Using Situational Intelligence to Create Support Characters in

Character-Centric Computer Games”, University of Dublin, Trinity

College, 2004

Part IV

Proactive Persistent Agent

Architecture (PPA)

wg. Brian Mac Namee

Using Situational Intelligence ..."

2

The Schedule Unit



Within a game world, NPCs created using the PPA

architecture must give the impression of having a life

beyond their association with players.



For example, a character might begin her day at home in the

morning, then go out to work, visit a bar after work and,

finally, return home again. Players should notice that NPCs

perform these different tasks, and in this way

the illusion

that characters have lives beyond their involvement with

players is created.



In order to achieve this, each NPC is given a schedule which

divides a simulation day into a

set of time periods, for each

of which it is indicated where the character should be and

how they should behave. The great advantage of using a

schedule is that it endows agents’ behaviour with a large

degree of believability, without requiring any sophisticated

computation.

wg. Brian Mac Namee

Using Situational Intelligence ..."

3

The Schedule Unit



In a typical example of a schedule, written in XML, an NPC

begins his day at home, assuming the AT-HOME role. This

would instruct him to:



sleep in his bed if he is tired,



go to his kitchen to make a sandwich if he gets hungry,



or, if he gets bored, go to his living room and watch a little TV.



At about 11:00 it is time for the character to go to work, where

he assumes the CHEF role, up to about 23:00. The CHEF role

places the character in a restaurant’s kitchen where he cooks

meals as required by his waiting staff. Finally, approaching

23:00 the NPC adjourns to his local bar for a few well earned

drinks before retiring home and repeating the process on

each subsequent day.

wg. Brian Mac Namee

„ Using Situational Intelligence ..."

4

Example of

a schedule

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Using Situational Intelligence ..."

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The Role-Passing Unit



The purpose of this unit is, not only to allow NPCs

display believable behaviour, but also, within a single

simulation, to allow them behave believably in a range

of diverse situations.



The description of this unit will begin with an

explanation of the motivations behind its inclusion,

and move on to a discussion of how it operates. The

latter will mention fuzzy cognitive maps (FCMs) which

are used to control an agent’s behaviour once a

particular role has been adopted.

wg. Brian Mac Namee

„Using Situational Intelligence ..."

6

The Role-Passing Unit



The purpose of this unit is, not only to allow NPCs display

believable behaviour, but also, within a single simulation,

to allow them

behave believably in a range of diverse

situations.



In order to satisfy the need for persistence, NPCs

controlled using the PPA architecture should be capable of

behaving believably in a range of diverse situations. If the

schedule shown before is considered, the character must be

seen at home, working in his kitchen and relaxing in a bar,

all within the same game.



The behavioural requirements of the NPC in each of

these situations are extremely different, and the

challenge of creating a single control system capable of

displaying all of these different behaviours is considered

beyond the capabilities of current AI techniques.

wg. Brian Mac Namee

„ Using Situational Intelligence ..."

7

The Role-Passing Unit

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Intelligence ..."

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

Technique of role-passing begins with a very simple agent

capable of assuming

different roles as it moves between

different situations. By assuming a new role, an agent

becomes capable of behaving believably in a new situation.



A role can be considered an

agent control system suitable

to a given situation, throughout which it dictates the

agent’s behaviour. By assuming and discarding roles as

appropriate it becomes possible to

create agents which

can behave believably in any number of situations. This sits

comfortably with the notion of situational intelligence, as

agents possess only enough intelligence to behave

believably in their given situation.

The Role-Passing Unit



Role-passing is closely related to the “old AI” idea - a

technique used for discourse understanding. This

technique involves writing scripts to describe the processes

involved in different situations.



Discourse understanding is made easier by the fact that,

once the current position in a script is determined, a

context for language understanding and the resolution of

ambiguity is created. The role-passing process is related to

scripts in that the behaviour of each agent within a

simulation is contextualised by the situation in which they

find themselves.

wg. Brian Mac Namee

„ Using Situational Intelligence ..."

9

The Role-Passing Unit

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„ Using Situational Intelligence ..."

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For example, a restaurant script would indicate that the

important actors in a restaurant situation are waiters,

customers and chefs; that the important props include

tables, menus, and food and that the sequence of events

upon a customer entering a restaurant proceeds with the

customer choosing a table, the waiter taking their order,

the food arriving and so on.

PPA Fuzzy Cognitive Control System



For the purposes of the PPA architecture, an FCM based

system - the proactive persistent agent fuzzy cognitive

control system (PPAFCCS) - has been created.



The PPAFCCS augments the original FCM system with a

number of node types which allow the input of activation

to the system from agents’ personal motivations and

perceptions of events in the game world, and for the

extraction of agents’ chosen behaviours.



Along with the original concept nodes, the

extra nodes

used within the PPAFCCS represent motivations, event

occurrences, rules, persistent flags and actions. When

these extra nodes are included in graphs they are referred

to as proactive persistent agent fuzzy cognitive maps

(PPAFCMs), rather than as FCMs.

wg. Brian Mac Namee

„ Using Situational Intelligence ..."

11

PPA Fuzzy Cognitive Control System



Motivations, rules and persistent flags always link

exclusively to concept nodes and never amongst each

other. Concepts output activation only to other

concept nodes, and action nodes. Similarly, action

nodes take input only from concept nodes, and very

rarely persistent flag objects.



Each concept is labelled and has a set of input links

(coming both from other concepts and nodes of the

other possible types) the activations of which are

summed and then passed onto a set of output links

emanating from the node.

wg. Brian Mac Namee

„ Using Situational Intelligence ..."

12

PPA Fuzzy Cognitive Control System



Motivation nodes allow the simulation of an agent’s

internal motivations. A motivation node maintains

two response curves, one which stores the manner in

which a motivation rises, and another for the manner

in which a motivation falls.



These

motivations can rise and fall regularly over

time (motivations such as hunger behave in this way),

or be affected by external events within a virtual world

(such as an increase in a fear motivation due to a

threatening occurrence nearby).

wg. Brian Mac Namee

„ Using Situational Intelligence ..."

13

Upward and

downward

motivation

response curves

used by a basic

hunger

motivation

wg. Brian Mac Namee

„ Using Situational Intelligence ..."

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