Kiko is a protocol-based agent programming model with operational semantics proving that agents written in it are protocol compliant and can enact any protocol.
How Computer Systems Embody Values
5 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 5representative citing papers
The paper defines four governance primitives for shared memory in multi-agent LLM fleets and reports evaluation results from a live production service.
CAAF uses recursive decomposition, formalized harnesses of invariants, and semantic gradients to enforce deterministic behavior in AI agents on commodity models.
Standard observables fail to support delegation-scoped attribution in agentic AI systems, requiring a new gateway and common information model to bind context at execution time.
Experts rate AI scenarios as more likely, less risky, more beneficial, and more valuable than the public, applying different weightings to risk versus benefit.
citing papers explorer
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Kiko: Programming Agents to Enact Interaction Protocols
Kiko is a protocol-based agent programming model with operational semantics proving that agents written in it are protocol compliant and can enact any protocol.
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Governed Shared Memory for Multi-Agent LLM Systems
The paper defines four governance primitives for shared memory in multi-agent LLM fleets and reports evaluation results from a live production service.
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Harness as an Asset: Enforcing Determinism via the Convergent AI Agent Framework (CAAF)
CAAF uses recursive decomposition, formalized harnesses of invariants, and semantic gradients to enforce deterministic behavior in AI agents on commodity models.
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Observability for Delegated Execution in Agentic AI Systems
Standard observables fail to support delegation-scoped attribution in agentic AI systems, requiring a new gateway and common information model to bind context at execution time.
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Perception Gaps in Risk, Benefit, and Value Between Experts and Public Challenge Socially Accepted AI
Experts rate AI scenarios as more likely, less risky, more beneficial, and more valuable than the public, applying different weightings to risk versus benefit.