Mechanism
Multi-agent contention is the condition in which two or more semantic agents simultaneously require access to the same substrate capability or the same temporal executability window. It is a structural consequence of shared substrate resources. The system does not treat contention as a scheduling conflict to be settled by a priority queue or by round-robin allocation. It treats contention as a capability-native condition: the resolution is computed by evaluating the forecasted executability of each contending agent's objective on the contended substrate and on alternative substrates, and then choosing an allocation on that basis.
This reframing follows directly from how capability is computed elsewhere in the disclosure. Capability is a determination that resolves an objective on a candidate substrate to one of a bounded set of outcomes: structurally possible, structurally impossible, structurally deferred, or rerouted. Contention resolution reuses that same determination across competing agents rather than introducing a separate arbitration vocabulary. The question is never whose request arrived first; it is which allocation of substrates and temporal windows lets the contending objectives remain executable.
Rerouting Before Allocation
The contention resolution process begins by evaluating, for each contending agent, the set of substrates on which that agent's objective can be executed and the temporal windows available on each substrate. This is the same per-substrate, per-window evaluation the capability layer already performs; contention resolution applies it across the contending set at once.
If a contending agent has an alternative substrate with equivalent capability and a compatible temporal window, the contention resolver reroutes that agent's objective to the alternative substrate. Rerouting frees the contended substrate for the agent that has no alternative. Contention is therefore dissolved rather than arbitrated wherever the substrate landscape permits it: an agent that can be served elsewhere is moved elsewhere, and the scarce resource is left to the agent for whom it is the only option.
The Allocation Decision
When rerouting cannot dissolve the contention, that is, when multiple contending agents have no alternative substrates, the contention resolver evaluates the forecasted executability impact of each possible allocation and selects the allocation that optimizes the system-level objective function. The allocation is chosen to optimize a declared system-level objective rather than to satisfy any single agent's preference.
The objective function is expressed in the capability layer's own outcome vocabulary. The candidate allocations are scored by which one produces the lowest aggregate non-synthesis rate, the shortest aggregate deferral time, or the highest aggregate uncertainty reduction across the contending set. These are the same quantities the forecasting and uncertainty machinery already computes for a single objective: non-synthesis is the failure to construct an executable form, deferral time is the wait until a forecasted executability window opens, and uncertainty reduction reflects confidence in the forecast. The allocation decision selects against that system-level measure rather than against arrival order or static priority.
Starvation Prevention
Resolving contention by forecasted executability could, on its own, leave an agent indefinitely deferred from a capability dimension it requires if the optimization repeatedly favors others. Starvation prevention guards against this. It imposes maximum deferral durations and escalation triggers that force reallocation or decomposition when an agent's deferral exceeds policy-defined bounds.
When the bound is exceeded, the escalation does not silently reorder a queue. It forces a structural action: reallocation of the contended substrate, or decomposition of the deferred objective so that the unsatisfied dimension is isolated to a sub-objective that can be routed to a different substrate. The deferral bound is policy-defined, so the point at which a long-deferred agent is escalated is a declared parameter rather than an emergent behavior.
Hoarding Prevention
The counterpart to starvation prevention is hoarding prevention, which ensures that no agent monopolizes a scarce capability dimension. It imposes maximum occupancy durations and fairness constraints that force an agent to release substrate resources after a defined execution period, even if that agent's objective is not yet complete.
Hoarding prevention and starvation prevention operate as the two bounds on a shared resource: one limits how long any agent may hold the contended substrate, the other limits how long any agent may be kept from it. Together they keep the forecasted-executability optimization from collapsing into a stable allocation that perpetually serves one agent at the expense of another, while leaving the underlying allocation decision driven by executability rather than by occupancy alone.
Resolution Architecture
The disclosed architecture organizes these elements as distinct modules. Two or more agents presenting overlapping capability demands to a shared substrate are the contending agents. They feed a contention engine that evaluates forecasted executability impact across alternative substrates for each contender. From the contention engine, the evaluation flows in parallel to a starvation prevention module, which enforces maximum deferral duration bounds and escalation triggers, and to a hoarding prevention module, which enforces maximum occupancy duration constraints and fairness-based release policies.
Both prevention modules feed an allocation decision module, which selects the allocation that optimizes the system-level objective function: minimizing aggregate non-synthesis rate, minimizing aggregate deferral time, or maximizing aggregate uncertainty reduction. The fairness bounds are therefore applied as constraints on the same allocation decision that the forecasted-executability evaluation drives, not as a separate scheduler bolted on afterward.
Relation to Negotiation and to Conventional Arbitration
Contention resolution is distinguished within the disclosure from the governed substrate resource negotiation that occurs before execution. Negotiation produces binding resource commitments that constrain the capability envelope's executability determination ahead of time; contention resolution resolves competing claims after they arise. The two are complementary: negotiation shapes the resource landscape in advance, and contention resolution settles the residual overlaps that negotiation did not pre-allocate.
Against conventional systems, the distinction is the capability-native treatment itself. Conventional shared-resource handling settles conflicts by priority queues or round-robin allocation, neither of which asks whether a contending objective remains executable at all on the resource it is waiting for. Here the contention is resolved by forecasted executability across the available substrates and temporal windows, so an agent that can be served elsewhere is rerouted and the scarce substrate is allocated to where it most improves the system-level executability outcome.
Disclosure Scope
The multi-agent contention resolution mechanism, comprising the evaluation of forecasted executability for each contending agent across the contended substrate and alternative substrates, the rerouting of any agent that has an alternative substrate with equivalent capability and a compatible temporal window, the allocation decision that selects among candidate allocations to optimize a system-level objective function expressed as aggregate non-synthesis rate, aggregate deferral time, or aggregate uncertainty reduction, and the starvation prevention and hoarding prevention bounds that impose maximum deferral durations, escalation triggers, maximum occupancy durations, and fairness-based release policies, is disclosed in the cognition filing (U.S. Application No. 19/647,395 and its international counterpart). This article describes that disclosed mechanism. The scope extends to embodiments in which contention arises over a substrate capability or over a temporal executability window, and in which the system-level objective function is realized over the disclosed executability quantities, provided the resolution remains driven by forecasted executability rather than by arrival order or static priority.
