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Battle Swarm: An Evolutionary Approach to Complex Swarm Intelligence

Battle Swarm: An Evolutionary Approach to Complex Swarm Intelligence. Russel Ahmed Apu Marina Gavrilova. Brief Outline. Battle Swarms Tactics and battle efficiency Swarm Intelligence: Missile Genotype Encoding Evolutionary strategies for battle swarms Experimental results and analysis.

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Battle Swarm: An Evolutionary Approach to Complex Swarm Intelligence

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  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. 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 Battle Swarms Agents

  5. Reaction Missile Reaction Radius Defense Mechanism Missile Missile Point Defense

  6. Actions of a Missile Action Encoding Set: {LRUDNMFAXYZ}* X=Rand Y=Converge* L= Roll LeftU=Pitch UpN=NOPF=Follow* Z=Diverge* R=Roll Right D=Pitch DownM=MemoryA=Avoid* PITCH UP Up ROLL RIGHT Constant Thrust Heading PITCH DOWN ROLL LEFT Right * Discussed in the next few slides

  7. 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

  8. Basic Sensory Encoding and Actions Proj(u) Proj(v) (2) Pitch up Avoid Target COG (1) Roll to match proj(v).proj(u)=0 Projection Plane

  9. Target Relative Coordinate(Range, Heading, Bearing)

  10. Target relative: Heading

  11. Target Relative: Bearing COG u Rproj b PRproj F Projection Plane

  12. Boids flocking: From left to right rules of cohesion, separation and alignment [2]. 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

  13. 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

  14. 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 LYUXLY

  15. 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]

  16. Basic Maneuvers [XF] [F] [U] [N] [LU] [A]

  17. 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

  18. Different Complex Maneuvering Tactical strategies • Diversion (b) Trail Wind Flocking • (c) Retaliation (d) Divergence

  19. 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]}

  20. 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)

  21. The Game: Co-evolution • Implement basic missile [F] and basic Turret {Select X, Fire@trajectory} • Adjust physical property to match • Fitness=50% (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)

  22. 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

  23. Results - Strategies evolved, Runtime and other aspects

  24. Evasive Dispersion Swarm: Distraction Trail Wind Assult Fitness Function 50 45 40 35 30 Feminine 25 20 15 10 5 0 0 20 40 60 80 100 Masculine No Randomization Randomized

  25. 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

  26. 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

  27. CONVERGENT Less defense turrets Draw less fire Easy to shoot down DIVERGENT More defense turrets Draw more fire Distracting and hard to shoot down Convergent VS Divergent Approach

  28. 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

  29. (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 Results

  30. Figure 11: Formation of Distraction, Organic and Deception pattern (g) Distraction 1: Early missiles draw fire (h) Distraction 2: Assault in progress (i) Organic motion pattern (j) Deception 1: Lead Assault (k) Deception 2: Overshooting the target (l) Deception 3: Come about and attack More Results

  31. More Results See Animation Demos

  32. 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

  33. 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)

  34. Runtime Performance

  35. 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

  36. Thank you

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