cs.MAOct 10, 2026
SaveJevolution: A Framework for Studying Communication and Collective Dynamics in AI Agents
Organizations: University of Waterloo
Abstract
Experiments with remote decision-making agents depend on more than the policy: the world may change during inference, the simulator determines which actions are available, and births and immigration alter who can act. We present Jevolution, an instrumented spatial predator-prey framework that makes these dependencies explicit. Its reference implementation separates the evolving world, asynchronous request scheduling, controller adapters, and experiment records. The model combines local observations, energy and resource constraints, predefined signals, and inherited scalar traits. We describe these mechanisms using the ODD protocol and distinguish implemented controls from research questions requiring additional interventions. Free synthetic fixtures exercise scheduling, signaling, and inheritance against the pinned implementation; they validate specified software behavior rather than model intelligence or ecological realism. A completed communication case study illustrates the end-to-end workflow using Jev to control both species. Across 6 complete habitat-seed pairs, the mean signals-on minus signals-off difference in normalized rabbit abundance was -0.0095 (nominal 95% pair-bootstrap interval [-0.0772, 0.0602]). This small study does not resolve the direction of the signal-system effect. The contribution is an inspectable experimental system and its evidence boundaries, not a new policy-learning algorithm or a demonstration of emergent language, adaptive selection, or biological predictive validity.
Figures & tables
Figure 1: Architecture of the pinned implementation. Arrows show information flow, not synchronous execution; world physics continues during requests. The controller receives local observations and engine-offered choices; the engine resolves routes and applies effects. Request identifiers join records across both paths. This schematic is not an empirical result, so no seed count or confidence interval applies.
Figure 2: Jevolution’s interactive interface. Left: run controls and population history. Center: habitat, animals, and signal markers. Right: the selected animal’s decision and state inspector. The image is reproduced unchanged from Figure 1 of the authors’ original manuscript, at 31.59 simulation seconds; it is not one of the twelve 90-s study runs. Visible signals illustrate the interface, not evidence of a communication benefit. Interface and artwork provenance are documented in Section 8 and Appendix K .
| Route | Supported operation and boundary |
|---|---|
| Run configuration | Seed, communication condition, timing settings, and audit runtime options. Predator–prey reset installs a fixed Jev roster: supplied provider, population, and group-delay roster edits are replaced. Arena roster configuration is a separate path. |
| Injected service | A host may replace choose while keeping the engine and observation builder. Synthetic responses test this boundary; virtual clocks additionally require the white-box harness described in Appendix C . |
| Source changes | New species, a supported clock port, receiver-only/fixed-trait controls, or policy optimization need additional implementation and validation. Frozen UI preview metadata is not an active experimental control. |
Table 1: Actual intervention routes on the frozen source. This is a source-backed capability map, not a usability experiment.
| Topic | Implemented basis | Evidence still needed for a scientific claim |
|---|---|---|
| Inference latency | Asynchronous requests, eligibility, deadlines, explicit clocks | A controlled delay intervention with matched policy, observation, and scheduling; population effects are not established by deadline tests. |
| Communication | Predefined messages; engine-enforced on/off mechanism | Receiver-only and cost-matched interventions to separate information use from energy/option changes. |
| Emergent behavior | Interacting agents, spatial resources, births, immigration | Repeated patterns and spatially matched nulls preserving resource attraction and demographic placement. |
| Natural selection | Inherited traits, ancestry state, and immigration counters; cohort reconstruction required | Cohort/lineage reproductive success and fixed-trait or inheritance controls separating mutation, drift, immigration, and selection. |
| Policy learning | Controller adapter boundary | A training loop, learning objective, and evaluation protocol; EPO is not implemented. |
Table 2: Research scope of the reference system. These are capability/evidence distinctions, not empirical estimates; no seed count or interval applies. The case study and synthetic checks are reported separately.
| Injected delay (ms) | Capacity 1 | Capacity 3 |
|---|---|---|
| 0 | 238 / 238 / 0 / 0 | 240 / 240 / 0 / 0 |
| 100 | 76 / 74 / 0 / 2 | 126 / 120 / 0 / 6 |
| 500 | 18 / 16 / 0 / 2 | 42 / 36 / 0 / 6 |
| 1000 | 10 / 8 / 0 / 2 | 24 / 18 / 0 / 6 |
| 1001 | 10 / 0 / 8 / 2 | 24 / 0 / 18 / 6 |
| 1500 | 6 / 0 / 4 / 2 | 18 / 0 / 12 / 6 |
Table 3: Synthetic runtime fixtures, not provider throughput: request/applied/late/cancelled counts per execution over 4.137 simulation seconds. Each cell was run for two seeds (42, 314159), each repeated twice; all four executions in a cell had the shown counts. There is no sampling-based interval for these deterministic fixtures. Capacity is per lineage, with three animals in each of two lineages. The acceptance deadline is 1,000 virtual wall ms, distinct from the live study’s 2,500 wall ms.
Figure 3: Communication worked example: all paired normalized rabbit-AUC effects and their mean. Each pair contains one 90-s run per arm. The nominal 95% percentile-bootstrap interval uses 10,000 whole-pair resamples (seed 20260928); few-pair coverage is unreliable. These are the same recorded runs as the communication-focused draft, not an independent replication.
Appendix figures & tables11 assets
Supplementary material from the paper’s appendix.
Appendix
Figure 4: Coordinates from retained world states for pair 01 (habitat seed 80350226): the shared initial state and the two terminal states at 90 simulation seconds. This is a visualization of recorded data, not a screenshot captured during execution. It shows one of the six pairs ( illustrated pair, two runs); the first numbered pair was chosen by index during figure preparation, after data collection, rather than by its effect or appearance. The terrain and initial animal coordinates match across arms. Markers show positions; overlapping markers can hide individuals. Food, energy, signals, and ancestry are omitted. No spatial hypothesis or clustering statistic is tested, so no confidence interval is attached; the aggregate paired estimate and uncertainty are reported in Figure 3 .
| System | Documented emphasis | Relationship to this implementation |
|---|---|---|
| NetLogo / Mesa [ Wilensky, 1999 , Masad and Kazil, 2015 ] | Environments and components for constructing agent-based models. | Jevolution supplies one specialized population task and a remote-decision execution/recording path; replacement of general ABM tools is not established. |
| Generative Agents, Project Sid, AgentSociety [ Park et al., 2023 , Altera.AL et al., 2024 , Piao et al., 2025 ] | Agent architectures, real-time social worlds, and simulation/intervention systems. | Real-time agent societies and framework-plus-intervention studies are prior art. This case uses a structured decision interface in a mechanistic population task. |
| flame / AgentTorch [ Chopra et al., 2024 ] | Differentiable agent-based models for calibration and action learning. | Jevolution does not differentiate through its world or optimize its controller in this study. |
| PettingZoo / Melting Pot [ Terry et al., 2021 , Leibo et al., 2021 ] | Explicit multi-agent interaction API; evaluation across social situations and partners. | The present service boundary is source-level and domain-specific; API compatibility and equivalent evaluation breadth are not established. |
| Jevolution | Pinned spatial engine, asynchronous requests, population turnover, signals, inherited traits, and joined records. | Evidence covers the declared software fixtures and one live-model communication intervention. Practical advantage over the systems above remains an open evaluation question. |
Table 4: Documented system emphases and this paper’s narrower reference task. These are literature/source descriptions, not measured comparative scores.
| Pair | Habitat seed | First arm |
|---|---|---|
| 1 | 80350226 | Signals on |
| 2 | 1766849094 | Signals on |
| 3 | 1976771215 | Signals off |
| 4 | 865173864 | Signals on |
| 5 | 1328634472 | Signals on |
| 6 | 415864476 | Signals on |
Table 5: Frozen main-study seed blocks and order. Six pairs were planned, with one attempted run per arm and no outcome-selected replacements. Actual completion is reported in the run ledger.
| Run | Time (s) | Req. | Applied | L/I/E/C | Usage ($) | Bound ($) | Status |
|---|---|---|---|---|---|---|---|
| E1+ | 2.0 | 20 | 20 | 0/0/0/0 | 0.0000 | 0.0000 | complete |
| E2- | 2.0 | 20 | 20 | 0/0/0/0 | 0.0000 | 0.0000 | complete |
| H01- | 90.0 | 900 | 900 | 0/0/0/0 | 0.0000 | 0.0000 | complete |
| H01+ | 90.0 | 900 | 900 | 0/0/0/0 | 0.0000 | 0.0000 | complete |
| H02- | 90.0 | 900 | 900 | 0/0/0/0 | 0.0000 | 0.0000 | complete |
| H02+ | 90.0 | 900 | 900 | 0/0/0/0 | 0.0000 | 0.0000 | complete |
Table 6: All attempted runs. L/I/E/C denotes late, invalid, error, and cancelled requests. Usage and per-run conservative bounds are derived from the paid-request ledger; free/engineering runs make no paid calls. These are not per-run invoices. Times are observed simulation horizons.
| Run | Wolf AUC | Founder surv. | R births | R deaths | R arrivals | Signals |
|---|---|---|---|---|---|---|
| P01- | 3.3617 | 0.400 | 141 | 103 | 8 | 0 |
| P01+ | 3.1830 | 0.500 | 151 | 106 | 8 | 191 |
| P02- | 3.8189 | 0.386 | 149 | 121 | 8 | 0 |
| P02+ | 3.3332 | 0.457 | 143 | 104 | 8 | 169 |
| P03- | 3.1411 | 0.429 | 147 | 104 | 8 | 0 |
| P03+ | 3.0703 | 0.457 | 135 | 104 | 8 | 222 |
Table 7: Secondary descriptive outcomes for all 12 main attempts. Wolf AUC is normalized by initial wolf abundance; rabbit founder survival is the fraction of initial rabbit IDs remaining at the fixed horizon. No secondary causal mechanism is identified and no extra hypothesis test is performed.
| Pair | On AUC | Off AUC | On off |
|---|---|---|---|
| pair-01 | 1.6974 | 1.7245 | -0.0271 |
| pair-02 | 1.6762 | 1.6677 | 0.0085 |
| pair-03 | 1.6028 | 1.5810 | 0.0218 |
| pair-04 | 1.6469 | 1.6192 | 0.0277 |
| pair-05 | 1.6734 | 1.6774 | -0.0039 |
| pair-06 | 1.7273 | 1.7530 | -0.0258 |
Table 8: Handwritten reference outcomes for 6 seed blocks. These are descriptive normalized rabbit-AUC values with immediate, zero-provider-latency decisions. The policy ignores received signals; its on/off differences can reflect emission cost. These runs are excluded from the main estimate and are not a matched comparison of model capability.
Figure 5: All 6 complete main-study seed pairs (12 runs), grouped by the frozen habitat seed. Each panel compares the two recorded arms for one initial state; provider responses and subsequent stochastic paths may differ. These descriptive traces do not establish ecological cycles or message-use mechanisms.
| Mechanism | Main-study setting |
|---|---|
| Rabbit recruitment | Maturity 8 s; minimum energy and water 30 each; global crowding scale 160 rabbits; hard birth cap 250; local crowding disabled. |
| Rabbit birth cost | Parent loses energy; birth or crowding rejection resets cooldown to s. Newborn energy/water: 60/80. |
| Wolf recruitment | Maturity 5 s; energy threshold 80; parent cost 30; birth cooldown 10 s; initial founder birth delay 20 s; birth cap 150. Newborn energy: 33. |
| Wolf energy | Metabolism 1.2 energy/s; a kill adds 40, capped at 100; movement energy charge is zero. |
| Movement | Rabbit speed tiles/s; wolf speed 1.6 tiles/s. Forest multiplies speed by 0.77; a wolf’s eating cooldown adds a factor 0.35. |
| Detection and capture | Rabbit sight radius ; wolf sight radius 9, or 2 for a rabbit hiding in forest. Capture distance ; eating cooldown 10 s; interference coefficient 1. |
Table 9: Effective parameters governing movement and demography. Trait symbols denote speed, vigilance, thrift, and fertility. Population caps constrain births, not immigration.
| Run | Obs. | Any | % | Danger | Food | Follow | R req/min | W req/min |
|---|---|---|---|---|---|---|---|---|
| P01- | 440 | 0 | 0.0 | 0 | 0 | 0 | 2.65 | 10.88 |
| P01+ | 439 | 148 | 33.7 | 105 | 46 | 0 | 2.44 | 11.49 |
| P02- | 403 | 0 | 0.0 | 0 | 0 | 0 | 2.46 | 9.88 |
| P02+ | 440 | 121 | 27.5 | 97 | 25 | 0 | 2.56 | 10.98 |
| P03- | 441 | 0 | 0.0 | 0 | 0 | 0 | 2.56 | 11.67 |
| P03+ | 439 | 162 | 36.9 | 146 | 18 | 2 | 2.70 | 11.89 |
Table 10: Signal exposure and population-normalized opportunities. denotes signals on/off. Type columns count rabbit observations containing each kind and are nonexclusive; help is absent. The final columns are rabbit/wolf requests per living animal-minute, not per wall minute or per eligible adult.
| Run/species | Obs. | Q (sim s) | Return n/N | W (wall ms) | Age n/applied | Age (sim s) |
|---|---|---|---|---|---|---|
| P01- R | 440 | 18.24/19.49 | 438/440 | 112.5/172.5 | 438/438 | 0.102/0.153 |
| P01- W | 439 | 3.46/7.80 | 439/439 | 107.5/154.9 | 438/438 | 0.101/0.152 |
| P01+ R | 439 | 19.03/22.98 | 439/439 | 116.0/170.9 | 439/439 | 0.102/0.153 |
| P01+ W | 439 | 3.11/7.63 | 438/439 | 107.3/152.1 | 435/435 | 0.101/0.152 |
| P02- R | 403 | 17.36/24.82 | 398/403 | 112.9/161.8 | 398/398 | 0.102/0.153 |
| P02- W | 453 | 3.64/9.44 | 451/453 | 108.6/156.8 | 446/446 | 0.101/0.152 |
Table 11: Per-run/species timing: R denotes rabbits and W wolves. Q is eligibility-to-dispatch queue delay; W in the time header is provider-adapter elapsed wall time. Time entries give median/95th percentile. Queue values are available for every listed observation. Return n/N explicitly excludes missing latency from quantiles; Age n/applied gives the matched-age denominator among applied requests. These are descriptive conditional distributions, not independent experimental samples.
| Run | Horizon (sim s) | On (elapsed s) | Off (elapsed s) |
|---|---|---|---|
| P01 | 90.0 | 90.067 | 90.106 |
| P02 | 90.0 | 90.110 | 90.064 |
| P03 | 90.0 | 90.107 | 90.056 |
| P04 | 90.0 | 90.091 | 90.106 |
| P05 | 90.0 | 90.183 | 90.122 |
| P06 | 90.0 | 90.051 | 90.062 |
Table 12: Recorded elapsed seconds for every original attempt. P: paid main; H: offline handwritten control; E: engineering check. On/off denote the signal mechanism. The horizon column is simulation time; the other columns are real UTC intervals. A dash means no such arm was attempted under that label.
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