Ensemble

ensemble@1 defines reducer-driven execution semantics for the Forge Pool execution platform.

Ensemble workloads combine multiple computational results, execution paths, models, scenarios, or candidate result surfaces into one deterministic canonical outcome.

Like every primitive family, ensemble@1 executes through the same public execution contract, deterministic execution doctrine, replay model, and verification framework.

Purpose

Ensemble execution is designed for workloads where confidence, stability, or decision quality emerges from combining multiple computational perspectives.

Representative domains include:

consensus generation
confidence fusion
multi-model comparison
scenario aggregation
disagreement analysis
stability evaluation
risk committee workflows

The primitive family defines composition semantics.

Execution profiles define the domain-specific aggregation behavior.

Operation Identity

Ensemble workloads are selected through the canonical execution contract.

json

{
  "op": {
    "name": "ensemble",
    "version": 1,
    "profile": "finance.credit.ifrs9_review_board.v1"
  }
}

Execution is submitted through the canonical endpoint:

http

POST /api/v0/ops/execute

ensemble@1 does not introduce a dedicated API surface.

Execution Characteristics

Ensemble execution is characterized by:

multiple component executions
controlled result composition
deterministic reduction
confidence-aware aggregation
disagreement measurement
contribution analysis
replay-compatible execution evidence

The execution platform may combine different computational sources while preserving deterministic composition semantics.

Representative Profiles

Representative ensemble@1 profiles include:

finance.credit.ifrs9_review_board.v1
insurance.board.risk.consensus.v1

Additional profiles may extend ensemble semantics without changing the public execution contract.

Execution Parameters

Ensemble profiles typically define parameters such as:

component result sources
aggregation strategy
weighting rules
confidence thresholds
disagreement criteria
contribution analysis configuration
artifact preferences

Each profile defines its own parameter schema while inheriting the shared ensemble@1 execution semantics.

Deterministic Execution

Ensemble execution remains deterministic under equivalent execution contracts.

Equivalent workloads must preserve equivalent:

component selection
composition rules
reduction behavior
confidence calculations
replay metadata
execution evidence

The order, location, and infrastructure used to produce component results must not alter computational meaning.

Reduction Semantics

Reduction is the defining characteristic of the Ensemble family.

Multiple intermediate results are combined according to profile-defined deterministic reduction rules.

Reduction may produce:

aggregated result surfaces
confidence bands
consensus outcomes
disagreement metrics
component contribution summaries
stability indicators

Reduction semantics are versioned and form part of execution truth.

Execution Evidence

Successful ensemble execution may produce:

component execution summaries
aggregation metadata
confidence metrics
disagreement measurements
result hashes
artifact references
replay metadata
verification outcomes

Execution evidence allows the final result to be inspected beyond the aggregated output alone.

Verification

Ensemble verification confirms that composition and reduction were performed according to the declared execution contract.

Verification may inspect:

component consistency
reduction behavior
weighting rules
confidence calculations
execution evidence
replay metadata

Verification validates composition semantics rather than implementation details.

Replay

Replay preserves the computational meaning of ensemble execution.

Replay depends upon:

operation identity
execution profile
component definitions
aggregation rules
deterministic reduction semantics
execution evidence

Equivalent ensemble execution contracts must preserve equivalent composition outcomes.

See:

Relationship to Other Primitive Families

Ensemble is one execution family within the broader Forge Pool execution taxonomy.

Unlike:

mc@1, which models repeated probabilistic sampling
graph@1, which models relationship-oriented computation
search@1, which models retrieval and ranking

ensemble@1 specializes in deterministic composition of multiple computational outcomes.

All primitive families share the same execution doctrine.

Relationship to Examples

Concrete Ensemble capabilities are documented in the Examples section.

Start with:

Examples demonstrate capability behavior.

This document defines primitive-family execution semantics.

Continue with:

Continue in Forge Studio

To explore Ensemble execution interactively:

Browse Ensemble capabilities in Capability Explorer
Inspect Ensemble execution blocks in Block Registry
Execute representative composition workflows
Review confidence outputs and execution evidence
Validate replay metadata and deterministic reduction

Trust should be established through independent verification rather than documentation alone.

Final Note

Ensemble is not a collection of independent runs.

It is a deterministic composition primitive implemented through the same canonical execution contract as every Forge Pool family.

By separating composition semantics from runtime implementation, Forge Pool enables complex multi-result reasoning while preserving deterministic execution, replay compatibility, execution evidence, and verification guarantees.

Ensemble ​

Purpose ​

Operation Identity ​

Execution Characteristics ​

Representative Profiles ​

Execution Parameters ​

Deterministic Execution ​

Reduction Semantics ​

Execution Evidence ​

Verification ​

Replay ​

Relationship to Other Primitive Families ​

Relationship to Examples ​

Related Documentation ​

Continue in Forge Studio ​

Final Note ​