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Survey Papers & Taxonomies

Academic syntheses of agentic patterns

Community · arXiv4 patterns
In Plain English

This page shows every pattern that Survey Papers & Taxonomies has published or written about — 4 in total. Each one includes a simple picture of how it works, a short explanation, an example of when to use it, and its trade-offs (the good parts and the not-so-good parts).

Reading patterns from one source at a time matters because it lets you see how a single company or team thinks about building AI agents, and compare their ideas side by side. If a pattern here also appears in the bigger Deep Catalogue, you will see a link so you can read the full, detailed version.

An open reference book with a pencil in the fold under warm lamp light

3C.01System-Theoretic Agent Patterns

SYSTEM-THEORETIC LAYERS Regulatorgoal tracking Reflexive Agentself-monitoring Digital Twinworld model Executoraction

Systems-level pattern language from Dao et al. (arXiv 2601.19752, Jan 2026) including digital-twin agent, reflexive agent, and layered regulators.

Use caseFraming agent systems beyond individual workflow patterns.
Trade-offsHigher abstraction · Less directly actionable.

3C.02Unified Taxonomy (6-Dimensional)

6-DIM TAXONOMY Autonomy · Adaptability Memory · Reasoning Social · Tool-Use

arXiv 2601.12560 classifies agents on six axes: autonomy, adaptability, memory, social, reasoning, tool use.

Use caseAgent portfolio classification, capability-gap analysis.
Trade-offsStructured comparison · Not a build-pattern per se.

3C.03Agentic RAG Survey

AGENTIC RAG VARIANTS RAG Single-Hop baseline Multi-Hop iterative Corrective self-heal

Singh et al. survey classifies agentic retrieval variants: single-hop, multi-hop, branching, corrective, self-reflective.

Use casePicking the right RAG topology for the task.
Trade-offsClarifies RAG design space · Survey, not prescription.

See 1C.10, 1D.15, 1D.16

3C.04LLM-Based Multi-Agent Survey

MULTI-AGENT COMMUNICATION Cooperativeshared goal Competitiveadversarial Hierarchicalsupervisor Consensusvote

Guo et al. (2024) synthesise communication patterns: cooperative, competitive, hierarchical, consensus.

Use caseDesigning inter-agent protocols.
Trade-offsCanonical classification · Survey-level detail.
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