Multi-tiered AI

Patrick Schmid

Multi-tiered AI

We already saw a presentation about this topic

Remember Ke‘s presentation? Short recap

Multi-Tiered AI Framework

The Intelligence Structure: Strategic Intelligence (SI) Operational Intelligence (OI) Tactical Intelligence (TI) Individual Unit (IU)

SI

OI

TI

IU

SI makes general goals and plans

OI is concerned with implementing the general orders from SITI Prepares the data for IU

Situational Projects

SPs: the basic messages for communications between different levels of AIs

OI1

SISP1

OI2OI1

SP2 SP2

TI2TI1 TI3

IU1 IU2 IUn…

The MTAIF Class Architecture

Unit Object

Empire Manager

Player Object

City Manager Objects

Player Object

Player Core (basic functionality)

Offensive Defensive Neutral

City Manager Object

Field Manager Objects

Field Manager Object

Unit Objects

SI

OI TI IU

package of functions and strategies

US Army

Soldier AI

All RTS games already have some rudimentary form

Follow orders Stay alive Report occurrences to the squad AI

(completed or failed orders, newly spotted enemies)

Select and engage targets Path finding

Squad AI

Already used in many games Receive orders from the platoon AI Translate them into soldier orders Distribute them to squad members Evaluate feedback from soldiers

New orders to soldiers Pass feedback to platoon AI

Most complex job: translating orders Move orders need to account for relative positions of

soldiers according to formation, terrain, posture More complicated orders are built by combining basic

ones, e.g. Move & Attack

Platoon AI

Similar tasks to squad AI Passing orders and feedback from one

level to the other Message translation is again the bulk

of the processing Individual squad‘s locations with

respect to rest of platoon is paramount concern

Company AI, Brigade AI, Division AI, Army AI, etc.

Similar to platoon AI, but dealing with bigger blocks of units

Formations are less rigid, allowing for more involved tactics

Highest level AI below computer player AI has extra duties: Each is assigned a different portion of the world

to operate in Passes upwards only important strategic

information Most tactical data is analyzed and acted upon in

this level

Computer Player AI (CPAI)

Many roles in RTS games: Civilization growth Construction Economics Research Politics Combat

Analyzes the relative strengths of the friendly and enemy troops and their disposition

Decide on overall strategy: attack or defend Deploy armies Adjust armies as combat progresses Reinforce

Augment decimated squads Build new armies

Example: Platoon AI

World War II Game Heavy firepower of tank Infantry’s better detection

ability Platoon AI decides

formation (triangle) Infantry engages enemy Tank supports with heavy

firepower

Example: Brigade AI Medieval Game Goal: capture fortress

defended by company strength enemy

Brigade AI approaches while staying out of engagement range

Two infantry companies attack in front

Cavalry goes behind fortress to cut off reinforcements and possibly attack from behind

One infantry company is held in reserve

Maps

Each AI needs its own map Why?

Plan paths Identify locations Implement tactics Each AI needs different information

Static map data, e.g. location of roads, updated only if a change occurs

Dynamic map data, e.g. troop locations, updated once or twice a second

Maps (cont.)

Element map Finest level of detail (~1 to 3 m squares) Some games: actual map element data Soldier’s path is calculated on this map Tracks actual enemy troops

Tile map Next level of detail (~10 m squares) Squad paths are calculated Troop data is represented only as combined

strengths

Maps (cont.)

Mega-Tile Map Platoon scale (~25-50 m) Finds paths for platoons

Larger Scale Maps You get the picture...

a) Platoon moves to defend a pass on the mega-tile map

b) Scout squad defends pass on the tile map

c) Scout soldier moves into trench on element map

Reference

Tom Kent “Multi-Tiered AI Layers and Terrain Analysis for RTS Games” AI Game Programming Wisdom 2