battlecode2014 - final presentation - group n.2

twoface - an intelligent Battlecode AgentFinal presentation - 23rd January 2015

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Battlecode final presentation - Group n.2

• Feature Overview • Communication

• Blackboard• Tasks

• Macromanagement• Opponent modeling• Strategy decision• Scouting• Squad Team• Guards

Outline

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• Micromanagement• Pathfinding

• Building period• Dynamic pathfinding• Agile pathfinding

• Testing• Experimental setup • Score measure• Experimental results

• Conclusion and future improvements

Battlecode final presentation - Group n.2 3

Blackboard● Task-oriented modeling of the

game actions● Public visible tasks● Dedicated tasks

Micromanagement● Enhanced individual attack

and defence● Retreat calculation

Macromanagement● Opponent model● Adaptive behavior● Scouts for distributed sensing● Enemy position representation● Leader guided squads for attack● Guarding groups for defence

Pathfinding● A* approach with map coarsening● Alternative bug pathing algorithm

with I.D.● Follow or flee from target algorithm● Determining good locations to build

PASTRs

Feature overview: twofaceintelligent and adaptive Battlecode playing agent


• Central aspect in battlecode• Essential for macromanagement• Example: coordination of units according to strategy• Exchanged data can be complex

⇒ Blackboard system with tasks

Communication

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Communication - Blackboard

Public Private

...

...

Bot A Bot B


• Task Interface • Defines only the most necessary methods

• Serialize the task object to the broadcast array• Deserialize the task object from the broadcast array• Task type to get the matched Implementation

• Allows a flexible way to define strategic commands• Can be used to outsource calculations to robots

Communication - Tasks

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• Implemented tasks: • ComputePASTRSpotTask• CreateMapTask• GuardPositionTask• ScoutAroundTask• SingleLocationTask• SquadTask

Communication - Tasks

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Macromanagement - Opponent Modelling

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INPUT

● Amount of Milk● No. of PASTRs ● No. of killed units● Braodcasting units● Position of enemies● No. of flocks

OUTPUT

● HerdingConfidence: likelihood the enemy is focusing on collecting milk

● AttackConfidence: likelihood the enemy is preparing for an attack;

Opponent behaviour classification in the class BehaviourControl.java

called every 25 rounds (=1 timespan)

} with scouts


Macromanagement - Opponent Modelling 2

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Defending Mode• PASTR built immediately• Guards are placed around PASTR

Attacking Mode• Squad team is formed• Enemy PASTRs are always attacked• Enemy HQ is blocked• PASTR building is postponed

Macromanagement - Strategy Decision

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Confindence timer to prevent frequent

switches


• Detect enemy location and movement → opponent modeling

• Two approachesa. senseBroadcastingRobots: most complete and fastest if radio

is used regularly by opponentb. soldier exploring area in map (senseNearbyGameObjects):

• slower• useful if no radio used by opponent• number of units is limited → reduced attacking power

Macromanagement - Scouting

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• Implementation• Task blackboard system• announced at start of match• scout in area between two given locations• if incoming attack detected: scouts help defending• enemy info broadcasted to radio channels:

• location• enemy ID• round number enemy detected

• Scout trajectory: 3 locations between HQ and enemy HQ

Macromanagement - Scouting 2

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Scouting

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• Formulated as a Task• Contains a channel• Same channel equals same team

• Leader• Leader sub-task automatically taken• Complex pathfinding• Detects blockades and reacts

• Follower• Will follow the leader as close as possible• Simple pathfinding• Complex pathfinding when lost

Macromanagement - Squad Team

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• Formulated as a Task• Contains a location and a channel• Same channel equals same team

• Communication• Broadcast information about nearby enemies• Support broadcaster

• Rallying• Rally around the goal• Maintain a distance to the goal• More defenses in direction of enemy HQ

Macromanagement - Guards

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• When enemies are encountered• Four Modes: Attack, Approach, Await, Retreat• Consider global and local advantages• Attack

• If in attack range and advantage is given• Or if in attack range and situation is hopeless

• Await• If slightly out of attack range and advantage is given

• Approach• If not awaiting and advantage is given

• Retreat• else (enemies nearby, no advantage, but not considered hopeless)

Micromanagement

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• A* search

• Coarsened map

• Advantages

• Fast pathfinding

• Disadvantages

• Long graph building period

• No navigation during

building

• No dynamic obstacle

avoidance

Pathfinding


• Graph is serializable• Outsource to SOLDIER using task system• Solves:

• Immobility during build period• Does not solve:

• Pathfinding during build period

Pathfinding - Building Period


• Search graph only incorporates walls• Solution: Bugging Algorithm• Solves:

• Dynamic Pathfinding• Pathfinding during build period

• Simply use greedy approach• Avoid walls when necessary

• Fails at long walls, nearby robots moving• Solution: “Iterative deepening bugging”

Pathfinding - Dynamic Pathfinding

Battlecode presentation of the Naive Agent - Group n.2

Pathfinding - Old vs. New


• Squads and Micromanagement need faster pathfinding

• Completeness is not an issue

• Two new Methods:

• Simple bug pathing, as seen at MIT

• Following, as greedy as possible

• Sophisticated and fast pathfinding by dynamically

switching between methods

Pathfinding - Agile Pathfinding


• 5 opponent players (reference player, 2014 finalists)• 9 maps (used to gain MIT course credit)• each player alternates between Team A and Team B• score measure

Testing - Experimental Setup

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mA : amount of milk by team A at end of match

mB : amount of milk by team B at end of match

mmax : amount of milk to win the game (107)

nend : number of rounds to finish the game

nmax : maximum number of rounds allowed

η : penalty factor [0,1] : sets lower bound on “rounds” feature

Testing - Score measure

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“milk” feature “rounds” feature


• beats reference player in all of the 9 maps• inferior to 2014 finalists• results of games against reference player:

Testing - Experimental Results

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• Ad hoc data structures for saving bytecodes• Improve the blackboard• More cooperation at micro-level• Improve the exploitation of the opponent modelling• More HQ modes (now only attacking and defending)• Define the conditions when to call the scouts • ...

Conclusion - Future improvements

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battlecode2014 - final presentation - group n.2

Documents

adaptive battlecode

battlecode essential

tasks communication

tasks micromanagement

enemy pastrs

opponent number of units

robots communication

macromanagement example