214 lines
8.4 KiB
Markdown
214 lines
8.4 KiB
Markdown
# Realism Improvements for Ant Simulation
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Research notes on real ant biology that could improve the simulation.
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Based on current literature through early 2026.
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## Current simulation model
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- 2 pheromone channels (toHome, toFood) with uniform deposition rate
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- 3-way sampling (ahead/left/right) for trail following
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- Random noise for exploration
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- Binary carrying state (has food or doesn't)
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- Uniform ant behavior (no individuality beyond ±20% scent storage)
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- Exponential decay + blur for pheromone diffusion
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## High impact, probably feasible on GPU
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### 1. Concentration-dependent pheromone deposition
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Real ants deposit up to 22x more pheromone near the food source vs near the
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nest (Lasius niger study, Springer 2024). They also modulate based on food
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quality — Pharaoh's ants deposit significantly more trail pheromone for 1.0M
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sucrose vs 0.01M sucrose.
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Currently `scentPerMarker` is constant (200). Making it decay with distance
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traveled since pickup (or scale with a food quality value) would produce more
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realistic trail dynamics. The concentration gradient effectively encodes
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distance information for other ants.
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Shader change: track steps-since-pickup in ant state, use it to scale
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deposition.
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### 2. Negative/repellent pheromone ("no entry")
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Pharaoh's ants deposit a repellent pheromone at trail junctions leading to
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unrewarding branches. Key details:
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- Lasts ~2x longer than attractive pheromone (~78 min vs ~33 min half-life)
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- Ants encountering it U-turn or exhibit zigzagging
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- Deposited specifically at bifurcation points, not along entire failed paths
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Source: Nature 438, 442 (2005)
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This would prevent the colony from getting stuck on depleted food sources.
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The alpha channel in the world texture is available for a 3rd pheromone type.
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Shader change: add repellent channel, deposit on failed searches or at
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depleted food, make ants U-turn on contact.
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### 3. Individual response thresholds (ant "personality")
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Real ants show consistent individual differences:
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- Bolder/more exploratory individuals become scouts, discover new food
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- Less exploratory individuals become recruits, exploit known trails
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- Scouts show lower responsiveness to trail pheromone
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- Recruits are highly attracted to trail pheromone and nestmates
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- These differences affect learning strategies (personal vs social info)
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Source: Frontiers in Ecology and Evolution (2021)
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The dominant model for task allocation is the "response threshold model" —
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each ant has a threshold for each stimulus. When pheromone concentration
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exceeds the ant's threshold, it follows; below threshold, it explores.
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Thresholds are determined by genetics, age, body size, experience, and
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spatial location.
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Shader change: pack a per-ant exploration/exploitation bias into the ant
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texture. Use it to modulate the balance between pheromone following and
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random walk.
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### 4. Adaptive stochastic noise
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In real colonies, noise prevents deadlocking onto suboptimal food sources.
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When a better source appears, noise is what allows some ants to discover it
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instead of all ants reinforcing the first trail found.
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Source: arXiv 1508.06816
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Could make noise level inversely proportional to pheromone strength — ants
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on weak trails explore more, ants on strong trails follow more tightly.
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This is a small change to the existing random walk logic.
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## Medium impact, moderate complexity
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### 5. Food quality encoding
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Real ants encode food quality in trail strength — the number of ants
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recruited scales directly with pheromone quantity released by returning
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foragers.
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Adding multiple food sources with different quality values would let ants
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deposit proportionally more pheromone for better food. The colony would
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naturally converge on the best source first, then shift when it depletes.
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Requires: food quality attribute per food cell, ants read it on pickup,
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store it, use it as a deposition multiplier.
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### 6. Alarm pheromone
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A separate fast-spreading, fast-decaying signal that causes nearby ants to
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either flee or swarm depending on context. Transgenic ant research mapped
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alarm pheromone processing to just 6 glomeruli — a sparse "panic button"
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with simple encoding.
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Could interact with obstacle placement or painted "danger zones." Would
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need a 4th pheromone channel or multiplexing with existing channels.
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Real compounds: formic acid + n-undecane in carpenter ants, pyrazines in
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Tetramorium. The blend ratio determines whether ants flee vs attack.
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### 7. Substrate-dependent pheromone decay
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Real pheromone half-life varies ~3x depending on surface type:
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- ~9 min on plastic
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- ~3 min on paper (Pharaoh's ant trail pheromone)
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- Temperature also accelerates degradation
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If the world had terrain types (encoded in unused bits of the world
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texture), pheromone could persist longer on some surfaces. This would
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create emergent preferred highway corridors on "good" terrain.
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### 8. Multicomponent pheromone blends
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Real pheromone signals are multicomponent blends, not single compounds.
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A single gland secretion can contain 32+ hydrocarbons, acids, aldehydes,
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etc. Different ratios trigger different responses — in Tetramorium,
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workers respond maximally to a specific 3:7 ratio of two pyrazine
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components.
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Could model as ratio between two co-deposited channels rather than
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single-channel signals.
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## Lower priority but fascinating
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### 9. Path integration
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Desert ants (Cataglyphis) maintain a running home vector — a cumulative
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sum of direction + distance traveled. This gives them a "home vector"
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pointing back to the nest at all times, even without pheromone trails.
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Key details:
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- The integrator resets at known locations (nest entrance, landmarks)
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- No cognitive map — it's a procedural "when you see this, go that way"
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- Ants can store multiple reference vectors to different food sites
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- Works even in featureless environments
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Source: Springer, Journal of Comparative Physiology A (2024)
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Shader change: accumulate displacement vector per ant, use it as fallback
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navigation when no pheromone detected.
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### 10. Tandem running
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One-to-one recruitment where a knowledgeable leader guides a naive
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follower:
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- Follower maintains antennal contact with leader's legs/abdomen
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- Leader only advances after being tapped (feedback loop)
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- Leader moves slowly so follower can learn landmarks
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- Follower can become leader after learning the route
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Source: Journal of Experimental Biology 223(9), 2020
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Hard to implement on GPU due to ant-ant interaction requirements, but
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would produce striking emergent behavior. Might need a CPU-side pass for
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pairing logic.
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### 11. Caste role switching via neuropeptides
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2025 Cell paper (Rockefeller): two neuropeptides — CCAP and NPA — control
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division of labor in leafcutter ants. Manipulating them turns defenders
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into nurses or gardeners into harvesters. Same molecular mechanism found
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in naked mole-rats (convergent evolution, 600M+ years).
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Could model as a continuous "role" variable per ant that shifts based on
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colony-level signals (ratio of foragers to scouts, food availability,
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threat level).
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### 12. Cuticular hydrocarbon (CHC) recognition
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Ants recognize nestmates via complex blends of dozens of cuticular
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hydrocarbons. Non-nestmates are attacked. This is relevant if the
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simulation ever has multiple colonies competing for resources.
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## Ant brain / connectome status (for reference)
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- No ant connectome exists yet
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- Drosophila adult connectome completed Oct 2024: 139K neurons, 50M
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synapses, 8,400+ cell types (FlyWire Consortium, Nature)
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- Clonal raider ant (Ooceraea biroi) reference brain published 2025
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(Rockefeller). TEM imaging for full connectome is underway
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- Ant antennal lobes have ~460 olfactory glomeruli vs ~50 in Drosophila,
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reflecting the centrality of chemical communication
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- Alarm pheromone processing maps to just 6 glomeruli — validates using
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simple threshold rules in simulation
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- 2025 PNAS paper describes ant colonies as "liquid brains" where
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heterogeneity in individual movement patterns (not uniformity) drives
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collective efficiency
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## Key sources
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- Pharaoh's ant pheromone modulation: ScienceDirect S0003347207002278
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- Spatial pheromone deposition in Lasius niger: Springer s00040-024-00995-y
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- Negative pheromone: Nature 438, 442 (2005)
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- Individual personality: Frontiers in Ecology and Evolution (2021)
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- Stochastic noise in foraging: arXiv 1508.06816
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- Drosophila connectome: Nature s41586-024-07968-y
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- Ant reference brain: Current Biology S0960-9822(25)01520-9
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- Neuropeptide caste control: Cell S0092867425005732
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- Path integration: Springer s00359-024-01725-2
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- Tandem running: JEB 223(9) jeb221408
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- Liquid brains: PNAS 2506930122
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