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 SI TI Prepares the data for IU

Situational Projects SPs: the basic messages for communications between different levels of AIs OI1 SI SP1 OI2OI1 SP2 TI2TI1TI3 IU1IU2IUn …

The MTAIF Class Architecture Unit Object Empire Manager Player Object City Manager Objects Player Object Player Core (basic functionality) OffensiveDefensiveNeutral City Manager Object Field Manager Objects Field Manager Object Unit Objects SI OITI 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