Post on 10-Feb-2016
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Battle Swarm: An Evolutionary Approach to
Complex Swarm Intelligence
Russel Ahmed ApuMarina Gavrilova
Brief Outline
• Battle Swarms• Tactics and battle efficiency• Swarm Intelligence: Missile Genotype Encoding• Evolutionary strategies for battle swarms• Experimental results and analysis
Objective:To utilize swarm based tactics & evolutionary
swarm strategies to increase tactical efficiency for offensive and defensive agents
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
Defense Mechanism
Missile
Missile
Missile
Point Defense
Reaction Radius
Reaction
Actions of a Missile
Constant Thrust
Right
Up
Heading
ROLL LEFT
ROLL RIGHT
PITCH DOWN
Action Encoding Set: {LRUDNMFAXYZ}* X=Rand Y=Converge*
L= Roll Left U=Pitch Up N=NOP F=Follow* Z=Diverge*
R=Roll Right D=Pitch Down M=Memory A=Avoid*
* Discussed in the next few slides
PITCH UP
Basic Sensory Encoding and Actions
COG
Follow Target
Projection Plane
(1)
Roll to match proj(v)=proj(u)
(2)
Pitch upProj(v)
Proj(u)
Basic Sensory Encoding and Actions
COG
Avoid Target
Projection Plane
(1)
Roll to match proj(v).proj(u)=0
(2)
Pitch up
Proj(v)
Proj(u)
Target Relative Coordinate(Range, Heading, Bearing)
x y zf ,f ,f Forward Vector of missile m Up vector of missile m Location of the missile m
Location of the Target
m
m
m
F
upT
= ===
=
rr
( )
( )
( )
( )
2x x y x z
2xx y y z
2xx z y z
f1- -ff -fff-ff 1- -ff=
f-ff -ff 1-Heading, mm ph F
é ùê úê úê úê úê úê úë û= ·
M
Mr
Range, pM TR -=
( ) ( )( )( )Bearing, mm mm mb FT p T pu u= × ·- -· ´M Mr r
Target relative: Heading
Target Relative: Bearing
COG
Projection Plane
u
PRproj
b Rproj
F
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
Boids flocking: From left to right rules of cohesion, separation and alignment [2].
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
Basic Encoding of Missile genotype • String of Possible Action (I.e [LYUXLY])• Action string is circular (iterative)• Missile DNA=Gene_String[]• Continuous execution of the string • Each action executed for an infinite time• Regulates Swarm Behavior/Tendency
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]
Basic Maneuvers
[N]
[A]
[U]
[F] [XF]
[LU]
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
Different Complex Maneuvering Tactical strategies
(a) Diversion (b) Trail Wind Flocking (c) Retaliation (d) Divergence
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]} Best{[FULLU], [FNLNU]}
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)
The Game: Co-evolution1. Implement basic missile [F] and basic Turret
{Select X, Fire@trajectory}2. Adjust physical property to match
– Fitness=50% (50% missiles hit the target)
3. Evolve Missiles and turrets against previous strain
4. Repeat step 3 for several Games cycles5. 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)
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
,i iiW W= J,i iiW W= J
# of missile hitting the target# of missiles launched
# of gunshots successfully evaded# of missiles destroyed+1
i
i
W =
=J
Results
- Strategies evolved, Runtime and other aspects
Fitness Function
05
101520253035404550
0 20 40 60 80 100Masculine
Fem
inin
e
Randomized No Randomization
Evasive
Dispersion
Distraction Swarm: Trail Wind
Assult
Complex Tactics: Convergent Approach
• Strength in numbers• Less exposure to incoming
fire• Increase of spatial threat• Decrease of temporal threat
• High Efficiency• Low evasion• Highly Masculine
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
Convergent VS Divergent Approach
• CONVERGENT• Less defense turrets• Draw less fire• Easy to shoot down
• DIVERGENT• More defense turrets• Draw more fire• Distracting and hard to
shoot down
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
More Results
(a) Funnel Shaped Assault
(b) Parachute Phase 1: Forming a moth ball
(c) Parachute Phase 2: Dispersing
(d) Parachute Phase3: Forming a Head
(e) Parachute Phase 4: Trail Wind Attack
(f) Divergent Attack
More ResultsFigure 11: Formation of Distraction, Organic and Deception pattern
(h) Distraction 2: Assault in progress
(g) Distraction 1: Early missiles draw fire
(i) Organic motion pattern
(j) Deception 1: Lead Assault
(k) Deception 2: Overshooting the target
(l) Deception 3: Come about and attack
More Results
See Animation Demos
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
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@ 50FPS !!!– Simulation runs upto 50 times faster
(FPS=2200+) is rendering is turned off (for evolutionary algorithm)
– Excellent Rendering quality (anisotropic texture mapping, particle engine)
Runtime PerformancePerformance of Different Runtime Modes
38.1698.72
391.74
48.77110.33
715.73
0
100
200
300
400
500
600
700
800
Mode
Fram
e/Se
cond
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
Thank you