[{"data":1,"prerenderedAt":131},["ShallowReactive",2],{"site-meta":3,"page-\u002Farchitecture":57},{"id":4,"title":5,"brand":6,"description":7,"extension":8,"footer":9,"lang":46,"locale":47,"meta":48,"nav":49,"organization":5,"stem":55,"__hash__":56},"site\u002Fsite.json","Resolution of Reality",{"name":5},"A decision-engineering framework. Decision capacity, not capital or talent, is the binding constraint in complex systems.","json",{"blurb":7,"columns":10,"copyright":44,"backToTop":45},[11,17,35],{"title":12,"links":13},"Framework",[14],{"label":15,"href":16},"Architecture","\u002Farchitecture",{"title":18,"links":19},"Modules",[20,23,26,29,32],{"label":21,"href":22},"M1 · Interest graph","\u002Farchitecture#m1",{"label":24,"href":25},"M2 · Option set","\u002Farchitecture#m2",{"label":27,"href":28},"M3 · Evaluator","\u002Farchitecture#m3",{"label":30,"href":31},"M4 · Compiler","\u002Farchitecture#m4",{"label":33,"href":34},"M5 · Governance","\u002Farchitecture#m5",{"title":36,"links":37},"Practice",[38,41],{"label":39,"href":40},"Projects","\u002Fprojects",{"label":42,"href":43},"About","\u002Fabout","© 2026 Resolution of Reality. Christian Nussbaum","Back to top ↑","en","en_US",{},[50,51,53,54],{"label":15,"href":16},{"label":18,"href":52},"\u002Farchitecture#arch",{"label":39,"href":40},{"label":42,"href":43},"site","nPYear1nVBPXUeOTCVu0siFEau5ghEy84pxxAtk_hNk",{"id":58,"title":59,"body":60,"description":124,"extension":125,"meta":126,"navigation":127,"path":16,"seo":128,"stem":129,"__hash__":130},"pages\u002Farchitecture.md","Agreement without aggregation",{"type":61,"value":62,"toc":121},"minimark",[63,87,113],[64,65,66,75,82],"title-block",{},[67,68,69,70,74],"p",{},"Agreement ",[71,72,73],"em",{},"without"," aggregation",[76,77,79],"template",{"v-slot:subtitle":78},"",[67,80,81],{},"An engine for resolving multilateral, sequential decisions",[76,83,84],{"v-slot:abstract":78},[67,85,86],{},"Many consequential decisions are multilateral and sequential: several self-interested actors must reach agreement, repeatedly, under uncertainty. This framework presents ƒ, an option-generation engine that resolves such decisions without collapsing the parties into a single objective. The engine is organised as five modules across three layers: representation, deliberation, and commitment. Interests are preserved in their native heterogeneity, options carry explicit feasibility witnesses, evaluations remain per-actor, and commitments are ratified as verifiable records.",[88,89,110],"arch-overview",{":commitments":90,":engine":91,":executions":92,":options":93,":reality":94,"caption":95,"captionLab":96,"commitmentsSub":97,"commitmentsTitle":98,"engineHead":99,"executionsSub":100,"executionsTitle":101,"heading":102,"markGlyph":103,"markLabel":104,"num":105,"optionsSub":106,"optionsTitle":107,"realityHead":108,"resolutionHead":109},"[\"ratified\",\"counterparties agreed\",\"threshold met\"]","[{\"title\":\"M1 · Interest graph\",\"sub\":\"structure interests\",\"terms\":[\"preferences\",\"trade-offs\",\"hard constraints\"]},{\"title\":\"M2 · Option set generator\",\"sub\":\"enumerate feasible\",\"terms\":[\"feasible configs\",\"witnesses\",\"assumption sets\"]},{\"title\":\"M3 · Evaluator\",\"sub\":\"score under uncertainty\",\"terms\":[\"per-actor scores\",\"confidence\",\"sensitivity\"]},{\"title\":\"M4 · Process compiler\",\"sub\":\"compile to DAG\",\"terms\":[\"task DAG\",\"checkpoints\",\"escalations\"]},{\"title\":\"M5 · Governance module\",\"sub\":\"ratify commitments\",\"terms\":[\"policy Π\",\"thresholds\",\"commitment C\"]}]","[{\"label\":\"task 1\",\"on\":3,\"total\":5},{\"label\":\"task 2\",\"on\":2,\"total\":5},{\"label\":\"task 3\",\"on\":1,\"total\":5}]","[{\"greek\":\"α\",\"text\":\"high consensus\"},{\"greek\":\"β\",\"text\":\"mid consensus\"},{\"greek\":\"γ\",\"text\":\"contested\"}]","[{\"title\":\"Actors\",\"sub\":\"who declares\",\"terms\":[\"principals\",\"agents\",\"stakeholders\",\"regulators\"]},{\"title\":\"Signals\",\"sub\":\"what they prefer\",\"terms\":[\"declared preferences\",\"revealed behaviour\",\"elicited priorities\",\"tolerance bands\"]},{\"title\":\"Constraints\",\"sub\":\"what is feasible\",\"terms\":[\"hard rules\",\"resource limits\",\"regulatory bounds\",\"governance\"]},{\"title\":\"History\",\"sub\":\"what was learned\",\"terms\":[\"prior commitments\",\"observed outcomes\",\"pattern priors\",\"failure modes\"]}]","The resolution function ƒ. The engine reads reality on the left (actors, signals, constraints, history), runs it through modules M1 to M5, and resolves it into options, commitments, and running executions on the right.","Figure 1.","signed promises","Commitments","Engine","running processes","Executions","Overview","ƒ","resolved","1","branching feasible space","Options","Reality","Resolution",[67,111,112],{},"The engine maps reality to resolution. Declared interests, revealed behaviour, and constraints enter on the left. The engine structures them into an interest graph, generates and scores a feasible space of options, and compiles the chosen option into a governed, executable process. Figure 1 gives the overall shape; the remainder of this framework specifies each module in turn.",[114,115,118],"arch-modules",{":modules":116,"heading":15,"num":117},"[{\"layerLabel\":\"Layer I\",\"layerName\":\"Representation\",\"id\":\"m1\",\"num\":\"2.1\",\"title\":\"Interest graph\",\"tag\":\"M1 · foundational\",\"body\":\"Structured representation of what each actor wants, trades off, and considers infeasible. Modelled as a weighted multigraph where nodes are actors, attributes, and goals, and edges encode preferences, trade-offs, and hard constraints. Interests are preserved in their native heterogeneity, never aggregated into a social welfare function.\",\"specInput\":\"actor declarations, revealed behaviour, elicitation signals, priors\",\"specOutput\":\"versioned interest graph \u003Cspan class=\\\"v\\\">G_t\u003C\u002Fspan>, per-actor projections \u003Cspan class=\\\"v\\\">G_t|a\u003C\u002Fspan>\",\"specOps\":\"query(actor), slice(goal), diff(t1, t2), update(signal)\",\"specDeps\":\"none, foundational\",\"feeds\":\"Consumed by \u003Ca href=\\\"#m2\\\">§2.2\u003C\u002Fa>, \u003Ca href=\\\"#m3\\\">§2.3\u003C\u002Fa>, \u003Ca href=\\\"#m4\\\">§2.4\u003C\u002Fa>, and \u003Ca href=\\\"#m5\\\">§2.5\u003C\u002Fa>.\"},{\"layerLabel\":\"Layer II\",\"layerName\":\"Deliberation\",\"id\":\"m2\",\"num\":\"2.2\",\"title\":\"Option set generator\",\"tag\":\"M2 · depends on M1\",\"body\":\"Constructs the space of feasible, executable configurations. Each option carries a feasibility witness and an explicit assumption set. Not a search returning a single optimum, but a structured, filtered option space with guarantees about coverage and feasibility.\",\"specInput\":\"\u003Cspan class=\\\"v\\\">G_t\u003C\u002Fspan>, constraint set \u003Cspan class=\\\"v\\\">C\u003C\u002Fspan>, generation policy \u003Cspan class=\\\"v\\\">π\u003C\u002Fspan>\",\"specOutput\":\"option set \u003Cspan class=\\\"v\\\">O_t\u003C\u002Fspan> = { (config, witness, assumptions) }\",\"specOps\":\"enumerate(π), filter(predicate), expand(option), invalidate(assumption)\",\"specDeps\":\"M1, constraint solver, combinatorial generator\",\"feeds\":\"Consumed by \u003Ca href=\\\"#m3\\\">§2.3\u003C\u002Fa> and \u003Ca href=\\\"#m4\\\">§2.4\u003C\u002Fa>.\"},{\"layerLabel\":\"Layer II\",\"layerName\":\"Deliberation\",\"id\":\"m3\",\"num\":\"2.3\",\"title\":\"Evaluator\",\"tag\":\"M3 · depends on M1, M2\",\"body\":\"Scores each option against each actor's projection of the interest graph, under an explicit uncertainty model. Output is a per-actor evaluation vector with point estimates, confidence intervals, and sensitivity decompositions, never a single scalar collapsed across actors. Deterministic given a fixed (\u003Cspan class=\\\"ital\\\">o, G_t, U_t, seed\u003C\u002Fspan>) tuple. The engine evaluates; it does not select. \u003Cspan class=\\\"ital\\\">o*\u003C\u002Fspan> is chosen by the actors and enters M4 as an input, not an output.\",\"specInput\":\"option \u003Cspan class=\\\"v\\\">o\u003C\u002Fspan>, interest graph \u003Cspan class=\\\"v\\\">G_t\u003C\u002Fspan>, uncertainty model \u003Cspan class=\\\"v\\\">U_t\u003C\u002Fspan>\",\"specOutput\":\"E(o) = { per_actor_score, confidence, sensitivity, risk_profile }\",\"specOps\":\"score(o), compare(o_a, o_b), stress_test(o, scenario)\",\"specDeps\":\"M1, M2, simulation runtime (MC \u002F Bayesian inference)\",\"feeds\":\"Consumed by \u003Ca href=\\\"#m5\\\">§2.5\u003C\u002Fa>.\"},{\"layerLabel\":\"Layer III\",\"layerName\":\"Commitment\",\"id\":\"m4\",\"num\":\"2.4\",\"title\":\"Process compiler\",\"tag\":\"M4 · depends on M1, M2\",\"body\":\"Compiles a selected option into an executable process, a directed acyclic graph of tasks with role assignments, checkpoints, preconditions, and escalation handlers. The module emits a specification; it does not execute. The specification is handed to an execution runtime and instrumented for observability.\",\"specInput\":\"selected option \u003Cspan class=\\\"v\\\">o*\u003C\u002Fspan>, actor role map \u003Cspan class=\\\"v\\\">R\u003C\u002Fspan>\",\"specOutput\":\"process DAG \u003Cspan class=\\\"v\\\">P\u003C\u002Fspan> with tasks, checkpoints, triggers, escalations\",\"specOps\":\"compile(o*), validate(P), trace(P, event_log)\",\"specDeps\":\"M2, M1\",\"feeds\":\"Consumed by \u003Ca href=\\\"#m5\\\">§2.5\u003C\u002Fa>.\"},{\"layerLabel\":\"Layer III\",\"layerName\":\"Commitment\",\"id\":\"m5\",\"num\":\"2.5\",\"title\":\"Governance module\",\"tag\":\"M5 · depends on M1, M3, M4\",\"body\":\"Installs the incentive and commitment scheme that makes the process durable under self-interested behaviour. Emits a versioned policy object specifying opt-in thresholds, penalty functions, reward contingencies, disclosure requirements, reversibility rules. Ratification is an explicit state transition producing a verifiable commitment record.\",\"specInput\":\"process \u003Cspan class=\\\"v\\\">P\u003C\u002Fspan>, evaluations \u003Cspan class=\\\"v\\\">E\u003C\u002Fspan>, actor commitment signals\",\"specOutput\":\"policy object \u003Cspan class=\\\"v\\\">Π\u003C\u002Fspan>, ratified commitment \u003Cspan class=\\\"v\\\">C\u003C\u002Fspan>, audit log \u003Cspan class=\\\"v\\\">A\u003C\u002Fspan>\",\"specOps\":\"ratify(Π), adjust(event), audit(C), revoke(C, trigger)\",\"specDeps\":\"M4, M3, M1\",\"feeds\":\"Terminal. Emits the ratified commitment record.\"}]","2",[67,119,120],{},"Five modules are arranged across three layers. Each module is a typed transform with explicit inputs, outputs, and dependencies. Two invariants hold throughout: interests stay native, and commitments stay verifiable.",{"title":78,"searchDepth":122,"depth":122,"links":123},2,[],"An engine for resolving multilateral, sequential decisions — five modules across three layers, with interests kept native and commitments verifiable.","md",{},true,{"title":59,"description":124},"architecture","0bbF2IVVzmmBQAJfBmYaPYe1CLHwJgGKYpkHMvTz-Eo",1781352216563]