ADR-376: Heterogeneous Agent Ensemble Composition API

Field	Value
Status	Proposed
Date	2026-07-27
Authors	claude (dream-cycle agent, 2026-07-27)
References	PoTRE (arXiv 2607.x, Kankariya & Arık); PRO-LONG (arXiv 2607.x, Fox et al.); Dream Cycle #2784

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Context

2026 agent-intelligence SOTA is defined by heterogeneous multi-agent ensembles. PoTRE (Poly-Topological Reasoning Ensembles) achieves 49.92% on Humanity's Last Exam by composing 4 agents with distinct reasoning strategies (adversarial refinement, hierarchical planning, spectrum search, direct chain) and a task-adaptive aggregation layer. This is grade-A reproduced (peer-reviewed arXiv 2607.x).

Ruflo currently supports homogeneous swarm topologies (hierarchical, mesh, hierarchical-mesh, adaptive) but provides no API for composing agents with different reasoning strategies within a single swarm. All agents in a Ruflo swarm share the same type/prompt template; topology controls communication pattern, not reasoning diversity.

Every major competitor (LangGraph v1.2.x, Microsoft Agent Framework 1.0, CrewAI v1.14.x) also lacks heterogeneous ensemble composition — making this an opportunity for differentiation at the coordination layer, not just a catch-up move.

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Decision

Add a heterogeneous topology mode to the Ruflo swarm system that:

1. Accepts a list of { strategy, agentType, weight } slots at swarm initialization
2. Assigns each slot a distinct reasoning prompt template (adversarial, hierarchical, spectrum-search, direct-chain) with no shared base prompt
3. After each task round, runs a task-adaptive aggregation step (weighted voting, configurable: majority / weighted / llm-judge) that synthesizes slot outputs into a single response
4. Records per-slot contribution scores in AgentDB for SONA-driven weight adjustment across rounds (leveraging existing EWC++ to prevent weight collapse)
5. Exposes CLI: npx ruflo swarm init --topology heterogeneous --slots adversarial,hierarchical,spectrum,chain --aggregation weighted

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Consequences

Positive:

• Enables PoTRE-class reasoning diversity within a single ruflo swarm invocation
• Reuses existing SONA, MoE, EWC++ infrastructure — no new learning subsystems required
• Opens a benchmark path: wire HumanityLastExam into ruflo performance benchmark --suite intelligence to measure parity with 49.92% PoTRE baseline

Negative / Risks:

• Aggregation step adds latency (~1 LLM call per round); must be async and time-boxed
• Per-slot prompt isolation complicates the existing shared memory namespace pattern — slots write to sub-namespaces, aggregator reads across them
• 4 concurrent agents per swarm round increases token cost ~4× vs single-agent baseline; must be documented in cost warnings

Not covered by this ADR (implementation-level):

• PRO-LONG programmatic memory log compression (separate feature, does not require new topology)
• Intelligence benchmark suite wiring (tracked in performance module roadmap)

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Alternatives Considered

• Parameter-sweep homogeneous ensemble: vary temperature/top-p across identical agents. Rejected — diversity of reasoning strategy (not just sampling) is what drives PoTRE gains.
• Separate CLI command ruflo ensemble: Rejected — heterogeneous is a topology variant; keeping it under swarm preserves the unified coordination model.
• No change: Accepted cost is falling behind as heterogeneous ensembles become the 2026 default for reasoning benchmarks.