A survey that unifies prior work on multi-agent LLM systems via the LIFE framework, mapping dependencies across collaboration, failure attribution, and autonomous self-evolution while identifying cross-stage challenges.
arXiv preprint arXiv:2410.11905 , year =
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
citation-role summary
background 3
citation-polarity summary
verdicts
UNVERDICTED 5roles
background 2polarities
background 2representative citing papers
Identifies concrete attacks from a malicious Provider on SAGA and proposes SAGA-BFT, SAGA-MON, SAGA-AUD, and SAGA-HYB mitigations offering different security-performance trade-offs.
The paper identifies twelve protocol-level security risks across MCP, A2A, Agora, and ANP and quantifies wrong-provider tool execution risk in MCP via a measurement-driven case study on multi-server composition.
DarwinNet is a tri-layered evolutionary network architecture that synthesizes intents into bytecode via LLM-driven adaptation and tracks maturity with a Protocol Solidification Index to achieve anti-fragility.
Proposes five foundational pillars and architectural patterns for building robust GenAI-native systems by combining AI with software engineering principles.
citing papers explorer
-
Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems
A survey that unifies prior work on multi-agent LLM systems via the LIFE framework, mapping dependencies across collaboration, failure attribution, and autonomous self-evolution while identifying cross-stage challenges.
-
Attacks and Mitigations for Distributed Governance of Agentic AI under Byzantine Adversaries
Identifies concrete attacks from a malicious Provider on SAGA and proposes SAGA-BFT, SAGA-MON, SAGA-AUD, and SAGA-HYB mitigations offering different security-performance trade-offs.
-
Security Threat Modeling for Emerging AI-Agent Protocols: A Comparative Analysis of MCP, A2A, Agora, and ANP
The paper identifies twelve protocol-level security risks across MCP, A2A, Agora, and ANP and quantifies wrong-provider tool execution risk in MCP via a measurement-driven case study on multi-server composition.
-
DarwinNet: An Evolutionary Network Architecture for Agent-Driven Protocol Synthesis
DarwinNet is a tri-layered evolutionary network architecture that synthesizes intents into bytecode via LLM-driven adaptation and tracks maturity with a Protocol Solidification Index to achieve anti-fragility.
-
Foundational Design Principles and Patterns for Building Robust and Adaptive GenAI-Native Systems
Proposes five foundational pillars and architectural patterns for building robust GenAI-native systems by combining AI with software engineering principles.