# Joint Control of Digital Swarms | Plasmatic Multitudes Source: https://mesmerprism.com/plasmatic-multitudes/shared-swarm-control.html Canonical HTML: https://mesmerprism.com/plasmatic-multitudes/shared-swarm-control.html Generated: 2026-07-24 Description: How several people can jointly shape one digitally native swarm through fields, rules, morphology, arbitration, provenance, and shared-body interaction. Markdown: https://mesmerprism.com/plasmatic-multitudes/shared-swarm-control.md Plain text: https://mesmerprism.com/plasmatic-multitudes/shared-swarm-control.txt BibTeX references: https://mesmerprism.com/plasmatic-multitudes/shared-swarm-control.bib CSL JSON references: https://mesmerprism.com/plasmatic-multitudes/shared-swarm-control.references.csl.json --- Shared swarm control | July 24, 2026 # Joint Control of Digital Swarms Several people shaping one many-part body A digitally native swarm can be a population of particles, agents, cells, points, instances, or field samples. It does not have to imitate a fleet of robots. Its parts may appear separately, gather into one body, dissolve into a field, divide, merge, disappear, or return in another form. Joint control asks what happens when several people act through that changing body at once. The problem is larger than giving each person a cursor. Participants may shape motion, local rules, density, morphology, boundaries, appearance, timing, or history. A system must decide where each intention applies, how overlapping intentions combine, what the autonomous swarm is allowed to change, and how the result remains attributable without reducing authorship to command counts. ## Central question How can several people share a transformable digital body without hiding the difference between individual influence, negotiated influence, and the body’s own autonomous response? The literature contains working examples of field superposition, weighted shared control, voting, persistent overwrite, and branching. It does not yet compare those policies within the same many-part body using common measures of agency, authorship, access, continuity, and expressive range. ## Particle bodies make control a boundary question A shared swarm body is both an interface and a way of staging the relation among people. The broader Plasmatic Multitudes argument begins with bodies whose edges can soften while their coherence survives. David Glowacki’s Isness work gives this question an explicitly social form. Participants appear as luminous energetic essences with diffuse boundaries in a shared virtual environment designed to loosen conventional self–other separation. The empirical study reports selected self-report similarities with psychedelic phenomenology, including connectedness and ego attenuation, but it does not establish that VR reproduces psychedelic states as a whole ([Glowacki et al., 2022](https://doi.org/10.1038/s41598-022-12637-z)). Glowacki’s later account describes a wider design space of weakly representational, light-energy bodies. Low structural specificity and low symbolic rigidity leave room for participants to project meaning into an intentionally under-specified form. In that setting, a boundary is not merely the outline of an avatar. It regulates how strongly a body reads as separate, how easily it can coalesce with another, and how much interpretation the representation invites ([Glowacki, 2024](https://doi.org/10.3389/frvir.2023.1286950)). John Desnoyers-Stewart’s sequence makes the particle-body side of this problem more operational. In Body RemiXer , tracked people appear as particle clouds and three-dimensional silhouettes. Touch connects their auras through a steady particle exchange, and body swapping superimposes one person’s aura onto another. In Star-Stuff , two participants meet as galaxies and constellations rather than humanoid avatars. Embodied Telepresent Connection uses particle-based aura avatars, cloud-like hearts, sound, simulated physics, and biosignal-linked feedback to support remote pseudohaptic touch ([Desnoyers-Stewart et al., 2020](https://doi.org/10.1162/leon_a_01925); [Desnoyers-Stewart, 2022](https://doi.org/10.1145/3532834.3536198); [Desnoyers-Stewart et al., 2023](https://doi.org/10.1145/3544549.3585843)). These works show why shared control cannot be treated only as command allocation. When a body carries intimacy, coalescence, or self–other ambiguity, an authority policy also shapes the experienced boundary. A participant may feel that a movement is mine, ours, negotiated, resisted, or produced by the system. The visual form alone cannot explain that difference. The system must expose who acted, what was accepted, what was transformed, and what the collective process did on its own. Evidence boundary ### Experiential precedent is not yet a control comparison Isness, Body RemiXer, Star-Stuff, and ETC establish that diffuse and particle-based bodies can remain meaningful, relational, and embodied. They do not compare locks, blending, field superposition, voting, or branching as multi-user authority policies. That control problem remains open. ## A digital swarm is a medium, not an unfinished robot Physical robots expose material constraints. Digital swarms expose a different design space. Particle systems made birth, change, and death ordinary operations of computational matter. Flocking models showed how local rules can produce coherent aggregate motion without scripting every trajectory ([Reeves, 1983](https://doi.org/10.1145/357318.357320); [Reynolds, 1987](https://doi.org/10.1145/37402.37406)). A digitally native swarm can extend those foundations without inheriting wheel dynamics, drone flight, battery limits, or a requirement to transfer to hardware. Its native operations may include birth, death, duplication, replacement, merge, split, resampling, graph rewiring, procedural growth, or conversion among particles, clusters, surfaces, and fields. It can move through non-Euclidean space, cross through itself, reverse time, or preserve incompatible outcomes as separate branches. Those operations are not convenient approximations of robot behavior. They define the ontology of the digital body. Robot swarms remain useful comparison systems because they force questions about collision, connectivity, communication loss, energy, maintenance, and physical safety. They are a later translation branch, not a maturity ceiling. A rigorous digital experiment should be judged by whether its participants, interaction, technical behavior, and interpretive claims match the digital substrate it addresses. ### Element An identified particle, agent, point, cell, or temporary local exception. ### Cluster A selected group, connected component, region, role, or moving sub-body. ### Body A macro-form whose coherence comes from common motion, density, response, or silhouette. ### Field A spatial influence, ambient condition, or distributed body without stable member identity. A single session may pass among all four. Changing scale therefore changes more than the camera zoom. It changes what kind of thing a person is controlling and what can count as continuity. ## Shared control is a stack of decisions “Collaborative,” “shared,” and “multi-user” remain vague until the system states who can affect what and what happens when intentions overlap. Robot-swarm research offers a useful command vocabulary. Kolling and colleagues distinguish behavior or algorithm selection, parameter setting, environmental influence, and influence through selected members or leaders ([Kolling et al., 2016](https://doi.org/10.1109/THMS.2015.2480801)). These categories describe ways human intent can reach a distributed process. They do not by themselves describe multi-user authority, morphology, representation change, or collaborative history. A broader digital system needs at least five separate decisions. Binding determines which people can affect which parts, regions, scales, roles, or functions. The control target specifies what they may change. Arbitration resolves simultaneous or conflicting intentions. Execution determines how local rules, constraints, or learned systems interpret an accepted command. Feedback and history show what happened, why it happened, and whether it can be reversed. ### What a participant may influence ### Motion and space Elements, subsets, leaders, regions, paths, attractors, repulsors, boundaries, obstacles, vector fields, and migration points. ### Rules and state Behaviors, local parameters, neighbour relations, state transitions, goals, constraints, cues, timelines, and autonomy levels. ### Body and history Density, silhouette, topology, birth, death, merge, split, representation, appearance, checkpoints, branches, replay, and repair. These targets can coexist. One person may shape a movement field while another edits density and a third controls when a proposed merge becomes permissible. Different inputs can also reach the same semantic action. A switch, a hand gesture, a line of text, or a pre-authored pattern can all issue a consequential command without pretending that the bodily acts are equivalent. ## How several intentions become one event Arbitration is not an implementation detail. It determines whether a shared body behaves like a collection of personal territories, a negotiated instrument, a majority system, an unstable compromise, or a field that preserves several forces at once. #### Scope separation Participants receive different agents, regions, scales, roles, or control dimensions. #### Lock or lease One person temporarily controls a target; ownership and expiry remain visible. #### Weighted fusion Continuous inputs are averaged or combined using explicit weights. #### Field superposition Spatial influences add, cancel, mask, or modulate one another. #### Vote or quorum A discrete transition waits for enough support or a recognized decision rule. #### Branch on conflict Incompatible proposals create parallel futures instead of one forced compromise. A seventh possibility is to retain conflict as visible motion: competing attractors, oscillation, seams, or local instability. Mass collaborative systems show that minority action, overwrite, competition, and repair can materially shape a collective result. They do not prove that participants will experience real-time swarm conflict as expressive rather than frustrating. That remains a design hypothesis ([Aleta and Moreno, 2019](https://doi.org/10.1140/epjds/s13688-019-0200-1); [Müller and Winters, 2018](https://doi.org/10.1371/journal.pone.0202019)). Mathematical influence is also not the same as felt agency. In virtual co-embodiment, paired participants shared one avatar through weighted averages. Participants could estimate their objective contribution, yet predictable movement could produce more agency than the control weight alone would suggest. A later study found that haptic feedback and weight distribution interacted with the task rather than improving agency in one simple direction ([Fribourg et al., 2021](https://doi.org/10.1109/TVCG.2020.2999197); [Venkatraj et al., 2024](https://doi.org/10.1145/3613904.3642425)). For a plasmatic body, the consequence is immediate: contribution weight, visible causal effect, perceived agency, bodily ownership, and authorship must be measured separately. A person may shape a transition without owning the resulting body, feel agency with little objective influence, or regard a sparse but decisive veto as their most meaningful contribution. ## Existing systems establish fragments of the design space The strongest evidence comes from several neighboring fields. Their boundaries matter as much as their contributions. Direct digital-particle precedent ### Entangled Up to eight smartphone users applied continuous gravitational influence and created persistent gravitational objects in one body of thousands of virtual particles. The system directly demonstrates simultaneous field influence, but its paper reports demonstrations rather than a controlled comparison of agency, fairness, or authorship ([Lee, 2021](https://doi.org/10.21428/92fbeb44.eae7c23f)). Shared-body bridge ### Co-embodiment Weighted avatar fusion provides controlled evidence about objective control, predictability, feedback, and agency. These studies concern one humanoid avatar, so transfer to a non-anthropomorphic swarm remains a testable proposition rather than an established result. Many-agent participation ### HuGoS and CrowdCollab HuGoS provides a browser-accessible environment for experiments with human and autonomous agents, detailed logging, signalling, and stigmergy. CrowdCollab lets collaborators plan a crowd from different perspectives. In both cases, the participants do not continuously co-control one transformable body ([Coucke et al., 2021](https://doi.org/10.1007/s11721-021-00199-1); [van den Bogaard et al., 2025](https://doi.org/10.1145/3689050.3706007)). Authoring and history ### Semantic control and branching Elemental Alchemist translates conceptual and semantic particle intentions into lower-level parameters, but it is a single-user system. PaintBranch preserves divergent versions of collaborative VR art as parallel branches; it does not automatically merge them ([Monteiro et al., 2026](https://doi.org/10.1145/3800645.3812946); [David et al., 2026](https://doi.org/10.1007/s42979-026-04980-z)). ### What the robot-swarm comparison contributes Multi-operator robot research makes authority transfer and resource sharing explicit. In Miyauchi, Lopes, and Groß’s paired study, operators normally controlled dedicated leader-centered teams and could send or request followers while the controller preserved connectivity. Robot sharing did not produce a simple task-performance win. Direct communication improved task score; sharing primarily reduced movement and energy and was perceived as useful ([Miyauchi et al., 2023](https://doi.org/10.1109/IROS55552.2023.10342457)). The useful transfer is organizational: fixed allocation, shared pools, temporary exchange, functional roles, overlapping scopes, hierarchy, and adaptive allocation are different ways of binding people to a population. The robots also retain local safety and connectivity constraints even when people redistribute authority. A digital body can borrow those distinctions without pretending that physical connectivity or robot ownership defines its expressive possibilities. Sharpened gap ### The mechanisms exist; the comparison does not Field superposition, weighted fusion, voting, persistent overwrite, and branch-on-conflict have all been implemented in real systems. No strong study found here applies several of them to the same transformable digital body with the same task, participants, feedback, and measures. ## A comparative programme for one shared body The first useful experiment is a comparison of authority policies, not a search for one supposedly natural interface. Two or three participants could guide one field-driven particle body through a short sequence: gather, divide, hold, yield, merge, recover, and re-individuate. The task should remain simple enough that a failure can be traced to a control policy, a mapping, a rendering, the autonomous solver, or social coordination. ### Control levels Direct subset manipulation, spatial-field influence, and rule or semantic control. Each level reaches the same body through a documented semantic command. ### Authority policies Visible short leases, weighted continuous fusion, field superposition, and branch-on-conflict. Policy order is counterbalanced. ### Body transitions Separate elements, temporary subgroups, one macro-body, an ambient field, and a renewed population. The study marks when continuity is preserved or lost. ### Participant awareness Active scopes, pending intentions, accepted commands, rejected or attenuated actions, and recent history remain inspectable throughout the session. ### Measures must follow the event Technical measures include input-to-acceptance latency, input-to-visible-effect latency, stability, command rejection, conflict frequency, participation concentration, solver cost, recovery time, replay accuracy, and morphological continuity. Task performance is useful, but it cannot establish meaningful participation or shared authorship by itself. Participant measures should separate agency, ownership, authorship, causal understanding, fairness, expressive range, collaboration, access cost, and willingness to preserve the result. Workspace-awareness research supports showing who is acting, where, on what, and what they are likely to do next ([Gutwin and Greenberg, 2002](https://doi.org/10.1023/A:1021271517844)). The Virtual Embodiment Questionnaire and Creativity Support Index offer useful components, but neither can be transplanted without adaptation: one assumes a virtual body, while the other does not measure causal authorship or authority ([Roth and Latoschik, 2020](https://doi.org/10.1109/TVCG.2020.3023603); [Cherry and Latulipe, 2014](https://doi.org/10.1145/2617588)). Mixed-ability participation makes this comparison more exact rather than peripheral. High-rate motion, speech, gaze, touch, switches, text, facilitated input, and pre-authored patterns should be able to reach meaningful semantic actions. A slower or intermittent contribution must not become less authoritative merely because it produces fewer events. The dedicated [Mixed-Ability Human-Swarm Interaction](https://mesmerprism.com/plasmatic-multitudes/mixed-ability-hsi.html) page develops the access, mapping, consent, privacy, refusal, and repair requirements for that work. ## An architecture for attributable transformation The human-facing system should send semantic intentions rather than raw controller events to the swarm. An intention records the participant, action, target, scope, desired timing, strength, duration, branch, uncertainty, and attribution policy. The authority layer then decides whether the action is accepted, transformed, delayed, combined, refused, or branched. The execution layer remains free to use particles, boids, fields, graph relations, state machines, procedural morphology, or learned policies. It must return more than the final animation. Participants need to know which elements were affected, which constraints changed the command, whether another intention interfered, and whether the result is continuing, complete, or failed. Minimum event record ### Keep four things separate - The intention a participant issued. - The authority or arbitration decision. - The command accepted by the execution layer. - The observed effect produced by the swarm and its constraints. This separation also makes undo and replay more honest. A collaborative undo should add a compensating historical event rather than silently erase evidence that an action occurred. Incompatible transformations may need branches instead of a forced merge. Periodic snapshots, semantic events, solver version, random seed, and dependency information make it possible to reconstruct how a form arose. Tölvera is a plausible open execution substrate for flocking, swarming, artificial life, OSC, and interactive mappings, though it has no native multi-user authority model. HuGoS provides a browser-delivered many-agent experiment pattern. Estuary demonstrates a shared generative process with different participant views. None is a turnkey solution; together they suggest a modular prototype with a semantic server, interchangeable arbitration, a particle or boid adapter, participant clients, and an append-only event log ([Armitage et al., 2024](https://nime.org/proceedings/2024/nime2024_71.pdf); [Ogborn et al., 2017](https://iclc.toplap.org/2017/cameraReady/ICLC_2017_paper_78.pdf)). ## Physical embodiment is a translation problem A later physical system does not have to reproduce every virtual particle. A small robot group might render landmarks, subgroup boundaries, direction, tension, or warnings while the digital body remains much larger. The semantic command and event history can persist while the embodiment changes. Translation must preserve authority, consent, attribution, and repair rights as well as movement. Physical robots add hazards and maintenance responsibilities that a reversible particle system does not have. Conversely, a robot test cannot validate instant topology change, branching history, interpenetration, or field-like embodiment when those are the research object. This is why physical validation remains one branch of the programme. It tests which semantic operations survive material constraints. It does not decide whether a digitally native collective body is legitimate. ## What the evidence supports ### Supported now - Several people can simultaneously influence one digital particle body through spatial fields. - Weighted shared control can separate objective contribution from perceived agency. - Digital particle systems can be controlled at conceptual, semantic, and technical levels. - Voting, overwrite, shared generative editing, and branching are implemented collaboration patterns. - Diffuse and particle-based bodies can support meaningful shared embodiment and social relation. ### Still open - Which arbitration policy best supports a particular expressive or cooperative task. - How agency and authorship survive transitions among agents, body, and field. - When visible conflict reads as expressive tension rather than loss of control. - How low-bandwidth participation remains consequential in mixed groups. - How a collectively authored body should be preserved, withdrawn, branched, or remixed over time. The central research object is therefore not a more efficient command panel. It is a body whose boundaries, internal organization, authority, and history can all become shared material. The body may transform the participants’ intentions as it executes them, but it should not hide that transformation. ## Sources Sources are grouped here by the claim they support. Robot, avatar, crowd, collaborative art, and creative-tool evidence are treated as related but non-equivalent. - Reeves, William T. "[Particle Systems—A Technique for Modeling a Class of Fuzzy Objects](https://doi.org/10.1145/357318.357320)." ACM Transactions on Graphics (1983). - Reynolds, Craig W. "[Flocks, Herds, and Schools: A Distributed Behavioral Model](https://doi.org/10.1145/37402.37406)." SIGGRAPH (1987). - Glowacki, David R., et al. "[Group VR Experiences Can Produce Ego Attenuation and Connectedness Comparable to Psychedelics](https://doi.org/10.1038/s41598-022-12637-z)." 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