⚠ AI-Driven Alpha Prototype — Experimental. May be misleading. For exploration only. ← Back to demos

Infancy Phase — BDH·DLiNoSS·HFF PID Brain ?INFANCY PHASE SIMULATION A dual-cage environment for evolving water-skidder creatures with merged BDH+DLiNoSS+HFF PID brains. Each cage contains a winged stickman body controlled by a tiny evolutionary neural controller that learns reflexive behaviors through reward-modulated Hebbian learning, oscillator banks, and forward-forward prediction. GOOD SIGNS: Smooth swimming motions, ripple patterns in the tank, reward trending upward, low jitter %. BAD SIGNS: Frozen creatures, >50% jitter, reward stuck negative, creatures pinned to walls. Drag particles to interact. Use sliders to tune.

Dual cage · tiny wings · amniotic fluid · fetal reflexes

Infant Goal Weights ?INFANT GOAL WEIGHTS Control the reward function that drives learning. Each weight scales a reward/penalty component in the fitness evaluation. Higher = more influence. These are the most important tuning parameters — they determine WHAT the creature learns to do. GOOD SIGN: Balanced weights producing varied smooth behaviors. Net reward trending upward, creature exploring its space. BAD SIGN: One weight dominating others causing stuck/repetitive behavior. Net reward flat at zero or negative for many generations. TIP: Start with defaults, then increase 'Wallow' for movement exploration or 'Stretch' for wing extension practice. Adjust gradually — large jumps reset learning.

Don't Hurt ?DON'T HURT — Pain Penalty Weight Scales how strongly wall-collision pain penalizes the creature's reward. High values make the creature very pain-averse, low values let it explore walls. GOOD SIGN: Creature avoids walls but still moves freely. Pain level near zero most of the time. BAD SIGN: Set too high and creature freezes in center (over-cautious). Set too low and creature repeatedly smashes into walls. The pain signal is a 3-timescale system: instant (contact), short-term (fading), long-term (cumulative). All feed into the penalty. Default: 1.00. Range: 0–2. High pain-aversion (>1.5) can suppress exploration. Zero means the creature ignores all pain. 1.00
Wall Avoid ?WALL AVOID — Proximity Gradient Penalty Penalizes the creature for being close to cage walls, even without touching them. Creates a gradient that pushes the creature inward. Only activates when wall proximity > 0.6 (inner 40% of the cage is a safe zone). GOOD SIGN: Creature stays in the central region with occasional wall approaches. BAD SIGN: Too high and creature is trapped in a tiny center zone. Too low and it hugs walls. Works as a soft boundary — complementary to Don't Hurt which is a hard collision penalty. Default: 0.25. Range: 0–2. Values above 1.0 create strong repulsion. Combine with Center weight for balanced positioning. 0.25
Center ?CENTER SEEK — Centering Reward Rewards the creature for positioning its center of mass near the horizontal center of the cage. Reward = 1 − (distance / half_cage_width). GOOD SIGN: Creature tends toward center but still explores outward occasionally. BAD SIGN: Too high = creature stays perfectly still at center (no exploration). Too low = creature drifts to edges. Works with Wall Avoid as a push-pull pair: Wall Avoid repels from edges, Center attracts to center. Balance them carefully. Default: 0.15. Range: 0–2. Typical useful range: 0.05–0.50. Set to 0 for free-roaming behavior. 0.15
Hiccup ?HICCUP — Periodic Twitch Reward Rewards the creature for making periodic body twitches at roughly 1.2 Hz (matching an internal sinusoidal reference). Encourages rhythmic muscle contractions like fetal hiccups. GOOD SIGN: Visible periodic body contractions, creature develops a rhythm. The oscillator bars show synchronized patterns. BAD SIGN: Too high = creature only twitches and never develops smooth movement. Too low = missed opportunity for rhythmic motor pattern learning. This is a developmental milestone — real fetuses hiccup to train respiratory muscles. Default: 0.10. Range: 0–2. Keep low (0.05–0.20) for subtle rhythmic training. Increase to encourage musical body oscillation. 0.10
Stretch ?STRETCH — Limb Extension Reward Rewards the creature for extending its limbs (sticks) toward their rest length. Measures the ratio of current length to rest length across all body sticks. GOOD SIGN: Wings and spine fully extended, body adopts an open posture. Stick stretch ratios near 1.0 in the sensor readout. BAD SIGN: Too high = creature strains to over- extend, possible instability. Too low = creature curls up into a ball. Stretch + Wallow together encourage graceful swimming motions — stretch opens the body, wallow rewards forward gliding. Default: 0.15. Range: 0–2. Works well in the 0.10–0.40 range. Increase for more wing-spread behaviors. 0.15
Wallow ?WALLOW — Gentle Movement Reward Rewards sustained, gentle movement (not too fast, not still). Uses a Gaussian bell curve centered at ~0.5 px/frame — the sweet spot of graceful wallowing motion. GOOD SIGN: Creature drifts smoothly through the medium with consistent slow speed. Beautiful ripple patterns in the tank. BAD SIGN: Too high = creature optimizes for constant speed and ignores other goals. Too low = creature is either frozen or frantic. Key reward for developing swimming behavior in the aquatic medium. Combines naturally with Stretch for elegant water-skidder locomotion. Default: 0.20. Range: 0–2. The most important movement reward. Start here when tuning for water-skidder behavior. 0.20
Withdraw ?WITHDRAW — Pain Avoidance Reward Rewards the creature for moving AWAY from the last wall it collided with. Teaches the association: pain → move in opposite direction. Only activates after a wall hit occurs, and measures whether the COM velocity points away from the hit wall. GOOD SIGN: After a wall bump, creature smoothly reverses direction. Quick recovery from pain. BAD SIGN: Too high = creature overreacts to wall contact with violent jerks. Too low = creature stays near walls after collision. A fundamental reflexive behavior — fetal withdrawal reflex. Pairs with Don't Hurt for complete pain-response learning. Default: 0.30. Range: 0–2. Keep moderate (0.20–0.50) for natural reflex. High values create twitchy wall-avoidance. 0.30

Presets ?PRESET SLOTS — Save & Recall Settings 8 slots to save and recall all your slider settings (physics parameters, goal weights, speed). CLICK empty slot: Saves current settings there. CLICK occupied slot (green): Loads those settings. RIGHT-CLICK occupied slot: Clears that slot. Presets persist in your browser's localStorage across page reloads. GOOD FOR: A/B comparison of configurations, saving a good baseline before experimenting, quickly switching between different training regimes (e.g., "explore" vs "settle" presets). The [Defaults] button resets all sliders to the original factory values without affecting presets. TIP: Save a preset before making major changes so you can always revert.

Physics Tuning ?PHYSICS TUNING Adjust the Verlet physics engine parameters that govern how the creature's body behaves in the aquatic medium. Changes apply immediately. These parameters are your main tool for fixing physics instability (jitter/tremor/twitching). GOOD SIGN: Smooth particle motion, sticks at rest length, jitter indicator at 0%. BAD SIGN: Particles vibrating, sticks stretching wildly, jitter >20%, body exploding. PRIMARY JITTER FIX: Increase Mass (adds inertia) and increase Damping (absorbs oscillation). SECONDARY: Decrease MaxSpd and Bounce. All changes are included when saving presets. TIP: If the body is jittering, try Mass=5+ and Damping=0.97+ first.

Mass ?MASS — Particle Inertia Sets the mass of all body particles. Higher mass = more inertia = smoother but slower motion. Mass directly affects Newton's F=ma — higher mass means the same torque produces less acceleration, reducing jitter and overshoot. GOOD SIGN: Body moves smoothly with visible momentum. Natural-looking inertial gliding. BAD SIGN: Too high = sluggish, unresponsive body that the brain struggles to move. Too low = twitchy, jittery motion from tiny forces. This is the #1 parameter for fixing jitter. Real water insects have surprisingly high mass relative to their muscle force. Default: 3.0. Range: 0.5–10. Jitter fix: try 5.0–8.0. Light/fast: 1.0–2.0 (may jitter). 3.0
Damping ?DAMPING — Velocity Retention Fraction of velocity retained each frame. 0.96 means 4% velocity lost per step. Lower = more drag = faster stop. Acts like viscous drag in the amniotic fluid. Critical for stability — too little damping and oscillations grow, too much and the creature cannot move. GOOD SIGN: Body glides to a smooth stop. Oscillations die out within a few frames. BAD SIGN: Too high (>0.99) = oscillations ring forever. Too low (<0.90) = body barely moves, feels stuck in molasses. Works with Mass: high mass + high damping = very stable but slow. Low mass + low damping = responsive but potentially unstable. Default: 0.96. Range: 0.80–0.999. Jitter fix: try 0.95–0.97. Aquatic feel: 0.94–0.96. 0.96
MaxSpd ?MAX SPEED — Velocity Clamp Hard limit on particle velocity (px/frame). Prevents particles from moving too fast and causing physics explosion or tunneling through cage walls. GOOD SIGN: Speed never hits the limit. Body moves freely within natural speed range. BAD SIGN: Particles constantly hitting speed cap = forces are too strong for current mass. Increase mass or decrease torque instead. This is a safety valve, not a tuning parameter. If you need to lower this to prevent explosion, the real fix is usually more damping or mass. Default: 40. Range: 5–200. Conservative: 20–30 (safe, limits exploration). Normal: 40–80. High risk: 100+ (may cause instability). 40
Bounce ?BOUNCE — Wall Collision Elasticity How much velocity is reflected when a particle hits a cage wall. 0 = perfectly inelastic (stops dead), 0.5 = half velocity reflected. GOOD SIGN: Soft wall contacts, creature slides along walls without bouncing away violently. BAD SIGN: High bounce causes the creature to oscillate between walls (ping-pong effect). Also worsens jitter near walls. Low bounce (0–0.05) is better for aquatic feel. Real water surfaces have very low elasticity. Default: 0.05. Range: 0–0.5. Recommended: 0–0.08 for water-skidder. Higher values create more energetic collisions. 0.05
W.Drag ?WATER DRAG — Medium Resistance Additional directional drag simulating water resistance on particle surfaces. Adds realistic aquatic friction beyond the global damping. GOOD SIGN: Body movements feel like swimming in a viscous medium. Natural deceleration curves. BAD SIGN: Too high = body freezes, cannot overcome water resistance. Too low = body moves like it's in vacuum (unrealistic). Combines with Damping: damping is a global velocity multiplier, W.Drag is extra drag proportional to speed in each direction. Default: 0.06. Range: 0–0.3. Light water: 0.02–0.05. Heavy medium (amniotic): 0.06–0.12. Thick gel: 0.15+ (very slow). 0.06
Tether ?TETHER — Center Pull Strength A weak spring force pulling all particles toward the cage center. Prevents the creature from permanently lodging itself in a corner. GOOD SIGN: Creature naturally tends toward center but can still explore edges freely. BAD SIGN: Too high = creature is rubber-banded to center, cannot explore. Too low = creature drifts to edges and stays there. This is a very subtle force — keep it low. It should be barely perceptible, just enough to break symmetry when the creature is stuck. Default: 0.005. Range: 0–0.05. Subtle: 0.001–0.005. Noticeable: 0.01–0.02. Strong (not recommended): 0.03+. 0.005
Paddle ?PADDLE — Wing Thrust Force Maximum thrust force the wing paddles can exert when activated by the brain. Higher = more powerful wing strokes, more ripple disturbance. GOOD SIGN: Wings produce visible ripples in the tank, creature can propel itself through the medium with paddle strokes. BAD SIGN: Too high = violent wing strokes cause body instability and jitter. Too low = wings flap but produce no useful thrust. This is the main locomotion force for the water-skidder concept. Balance with Mass: Paddle/Mass ratio determines acceleration. Default: 180. Range: 10–500. Gentle: 50–100 (subtle movement). Normal: 150–250 (visible propulsion). Powerful: 300+ (may cause instability). 180

Brain & Physics Analytics ?REAL-TIME ANALYTICS VIEWER Zoomable, pannable view of ALL internal brain and physics signals with live FFT spectrograms and VU-bar level meters. MOUSE CONTROLS: • Scroll wheel: zoom in/out (toward cursor) • Left-drag: pan the view • Right-click: choose a preset view BUTTONS: • Home: reset zoom/pan to default • Fit: auto-fit all content to screen DOWNSAMPLING: When running at high speed, the downsampler prevents aliasing artifacts in the FFT display. "Skip" is fast (just decimates), "AA" applies a box filter for accurate spectral analysis. 15 preset views cover every aspect of the brain constellation: DLiNoSS oscillators, BDH Hebbian, HFF forward-forward, PID gains, reward breakdown, wing dynamics, and more.

?HOME resets pan & zoom to the default origin. All signal strips return to their natural position. ?FIT auto-scales to show all visible content within the analytics canvas. ?PRESETS: Switch between signal groups (FFT strips, VU bars, neural graph) and 3D trail views (waterfall, stack, orbit). Waterfall: signals recede into vanishing point Stack: layered 3D waveforms with filled shadows Orbit: phase-space XY trajectories Also accessible via right-click context menu. ?DOWNSAMPLING factor (1-64). At high sim speed, reduces the number of samples stored in the ring buffer. Factor N means keep 1 in every N samples. Prevents FFT aliasing at >100x speed. ?DOWNSAMPLE MODE: Skip: fast decimation, keeps every Nth sample. May introduce aliasing (educational!). Phase slider available to shift the sample pick. AA: anti-aliased box filter averaging. More CPU but spectrally clean. No phase slider (all samples contribute).
SIM HEALTH:

3D Neural Graph ?INTERACTIVE 3D NEURAL VISUALISATION All ~118 neurons shown as spheres in force-directed 3D layout. Layers: Input → DLiNoSS → BDH → HFF → PID-mix → Output. Animated flow dots show spike events (orange) and sampling streams (blue) along connections. MOUSE CONTROLS: • Left-drag: orbit / rotate • Scroll wheel: zoom in/out • Right-drag: pan Node colour = PID channel assignment. Brightness pulses on spike detection. DRAG a node to pluck-learn: perturbs brain weights!

3D Usability Layout Monitor ?INTERACTIVE USABILITY ERGONOMICS MAP Force-directed 3D graph of ALL interactive UI elements. HOW IT WORKS: • Every click, slider drag, or select change is tracked • Mouse travel distance between interactions is recorded • Items used one after another attract each other • High mouse travel distance pushes items apart NODE BRIGHTNESS: more used = brighter glow NODE SIZE: proportional to total usage count EDGES: connect items used in sequence — thicker edges = more frequent transitions This is a gravitational UI optimiser — frequently co-used controls naturally cluster together, revealing ergonomic improvement opportunities. DRAG nodes to manually explore layouts. The graph self-organises from your actual usage patterns. GOAL: items that are clicked together should be neighbours — minimising cognitive navigation load.

AI Assistant ?EMBEDDED MCP-AWARE AI ASSISTANT Continuous-learning assistant that tracks everything: HOW IT WORKS: • Every interaction, parameter change, and conversation is logged as JSONL checkpoint events with Unix timestamps • Knowledge accumulates from your usage patterns • Conversations are correlated with tracked interactions • Model fingerprints ensure parameter consistency CHECKPOINTING (Ⓒⓚ2026afrtNL): • ⬇ Export: Download a .jsonl checkpoint file • ⬆ Import: Load a previously exported checkpoint • Server-side merge: Combine multiple checkpoints using npx tsx merge-checkpoints.ts JSONL FORMAT (MCP Protocol): Each line is a jsonrpc 2.0 message with: timestamp, copyright, model fingerprint, type, payload The assistant learns WHY and WHAT changed by correlating conversations with interactions over time windows.

Spectral Learning EQ ?SPECTRAL LEARNING EQUALISER Three-band control over the learning rate multiplier. DC (bias): Constant multiplier applied to all BDH Hebbian and HFF forward-forward learning. 0 = no learning, 1 = normal, 2 = double speed. 1st Order (gradient): Scales learning by the first derivative (trend) of recent reward. Positive = boost learning when reward is rising. Negative = boost when reward is falling. 2nd Order (curvature): Scales learning by the second derivative (curvature) of recent reward. Positive = boost at reward acceleration. Negative = boost at reward deceleration. Combined: mul = DC + 1st·gradient·10 + 2nd·curvature·50 Clamped to [0, 4] for safety.

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