Battle Swarm: An Evolutionary Approach to Complex Swarm Intelligence

1
Battle Swarm An Evolutionary Approach to Complex
Swarm Intelligence

• Russel Ahmed Apu
• Marina Gavrilova

2
Brief Outline

• Battle Swarms
• Tactics and battle efficiency
• Swarm Intelligence Missile Genotype Encoding
• Evolutionary strategies for battle swarms
• Experimental results and analysis

3
Objective

• To utilize swarm based tactics evolutionary
  swarm strategies to increase tactical efficiency
  for offensive and defensive agents

4
Battle Swarms Agents

• MISSILES
• Autonomous
• Limited sensory capabilities
• Limited intelligence
• Single objective Hit ship
• Complex dynamic system
• Behavior of one missile effect other missiles in
  the swarm
• Evolutionary Strategy

• DEFENSE TURRETS
• Point Defense system
• Only Visual/radar capabilities
• Limited coverage
• Single Objective Destroy missiles
• Simple rule, complex outcome Select and fire
• Behavior and efficiency cruicial to survival
• Fixed Strategy

5
Defense Mechanism
Reaction
Missile
Reaction Radius
Missile
Missile
Point Defense
6
Actions of a Missile
Action Encoding Set LRUDNMFAXYZ
XRand YConverge L Roll Left UPitch Up
NNOP FFollow
ZDiverge RRoll Right DPitch Down
MMemory AAvoid
PITCH UP
Up
ROLL RIGHT
Constant Thrust
Heading
PITCH DOWN
ROLL LEFT
Right
Discussed in the next few slides
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Basic Sensory Encoding and Actions
Follow Target
COG
Proj(u)
(2) Pitch up
Proj(v)
(1) Roll to match proj(v)proj(u)
Projection Plane
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Basic Sensory Encoding and Actions
(2) Pitch up
Avoid Target
COG
(1) Roll to match proj(v).proj(u)0
Projection Plane
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Target Relative Coordinate(Range, Heading,
Bearing)
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Target relative Heading
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Target Relative Bearing
COG
u
Rproj
b
PRproj
F
Projection Plane
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Swarm Relative Encoding

• Regulates the probability of Flocking Tendency
• Y Flock and increase tendency (probability ? of
  Boids flocking)
• Z Diverge from flock and decrease tendency
• If an agents decides to flock (prob ?), the
  direction is determined using modified BOIDS

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Decision Making

• Event related decision are made by the swarm
  implicitly
• Avoiding Incoming fire Ionization trail gives
  negative pheromone to allow flocking out of a
  region
• Finding Weakness in Defense Combined usage of
  flocking tendency, gas and ionization pheromone
  trail

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Basic Encoding of Missile genotype

• String of Possible Action (I.e LYUXLY)
• Action string is circular (iterative)
• Missile DNAGene_String
• Continuous execution of the string
• Each action executed for an infinite time
• Regulates Swarm Behavior/Tendency

LYUXLY
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Encoding Basic Maneuvers

• Maintain Current Heading N
• Homing the Target F
• Ring Motion U
• Cork Screw LU, LUMMM
• Evasive Approach XF, XMMMF
• Basic Evasive Action A, AMMMX
• Fall Back XU, XMMMU, AU
• Scramble X

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Basic Maneuvers
XF
F
U
N
LU
A
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Different Complex Maneuvering Tactics

• Retaliation frontal attack
• Evasive avoid fire at all costs
• Convergent approach approach target from a
  particular direction
• Divergent approach surround and approach from
  different directions
• Trail wind flocking one missile leads others
• Distract and draw fire

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Different Complex Maneuvering Tactical strategies

• Diversion (b) Trail Wind Flocking
• (c) Retaliation (d) Divergence

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Mutating and Evolving the Missile Genotype

• Fitness Define a fitness function for the
  desired action
• Crossover Augment/concatenate Genes
• LUMU AMD ?LUAMDMU LUMD AMDUMU
  LMDMU
• Randomization Replace arbitrary symbols with
  X run the simulation and convert meta genes to
  real genes
• FFLLU ? FXLXU ? FULLU, FFLFU, FNLNU,
  FMLNU ? BestFULLU, FNLNU

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Induced Evolution

• We can introduce certain desired behavior in
  addition to natural evolution
• Step 1 Train Missiles separately to obtain
  certain desired behavior without any other
  consideration. Obtain Viral strain W
• Step 2 Infect All current Genotype with viral
  Strain W (crossover)

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The Game Co-evolution

• Implement basic missile F and basic Turret
  Select X, Fire_at_trajectory
• Adjust physical property to match
• Fitness50 (50 missiles hit the target)
• Evolve Missiles and turrets against previous
  strain
• Repeat step 3 for several Games cycles
• If fitness falls or rises dramatically increase
  physical strength of opposing swarm (Missile
  Acceleration, velocity, turning. Turrets Speed
  of fire, number of turrets, firing frequency)

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The Fitness Function Hetero-Sexual Mating

• Use a two dimensional Fitness Function
• Every missile has a masculine and a feminine
  fitness
• Masculine Ability to Attack
• Feminine Ability to Survive

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Results

• - Strategies evolved, Runtime and other aspects

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Fitness Function
50
45
40
35
30
Feminine
25
20
15
10
5
0
0
20
40
60
80
100
Masculine
No Randomization
Randomized
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Complex Tactics Convergent Approach

• High Efficiency
• Low evasion
• Highly Masculine

• Strength in numbers
• Less exposure to incoming fire
• Increase of spatial threat
• Decrease of temporal threat

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Complex Tactics Divergent Approach

• Cause more distraction and confuse the defense
  system
• Less likelihood for a missile to draw fire
• Decrease of spatial threat
• Increase of temporal threat

• Lower Efficiency
• Highly Evasive
• Highly Feminine

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Convergent VS Divergent Approach

• DIVERGENT
• More defense turrets
• Draw more fire
• Distracting and hard to shoot down

• CONVERGENT
• Less defense turrets
• Draw less fire
• Easy to shoot down

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Complex Tactics Trail Wind Flocking

• Better than Convergent Approach
• Least exposure to incoming fire
• Lot of opportunity for diversion/distraction
• Decrease of spatial threat
• Decrease of average temporal threat

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More Results
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More Results
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More Results

• See Animation Demos

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Rendering and Physical Engine

• Regular physics engine will not suffice
• Approximation aggravates trajectory computation
• Construct everything from scratch
• Advanced look-ahead estimation based physics
  engine
• Robust Rendering engine
• Anisotropic Texture filtering
• Multiple LOD based geometry rendering
• Particle engine
• Highly optimized exclusive API for performance
• Flexibility

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The Simulation Engine

• Robust design Separation of Rendering modules
  from the simulation
• Implements Command Console
• Runtime performance is highly efficient
• For 50 missiles
• Full quality rendering_at_ 50FPS !!!
• Simulation runs upto 50 times faster (FPS2200)
  is rendering is turned off (for evolutionary
  algorithm)
• Excellent Rendering quality (anisotropic texture
  mapping, particle engine)

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Runtime Performance
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Summary

• Using Swarm Intelligence to evolve battle tactics
  for
• Missiles
• Point Defense Turrets
• Evolutionary strategies
• Gene_String evolution
• The novel Induced Evolution strategy
• Co-evolutionary strategy
• Implementation
• Rendering and physical Engine
• Genotype encoding
• Basic maneuvers
• Complex maneuvers
• Integration

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Thank you