
As autonomous artificial intelligence (AI) agents increasingly interact across decentralized networks, traditional communication protocols (e.g., HTTP, MCP) fail to provide intrinsic execution control, semantic validation, and liability boundaries. This paper introduces the Catalyst Intelligence Operating System (CIOS) and its core communication layer, the Onto-Protocol. Unlike transport-focused standards, the Onto-Protocol is a semantic contract framework designed to define agent intent, strictly enforce execution boundaries, and generate cryptographically verifiable audit trails. Furthermore, we present the CIOS Probabilistic Trust Model—a dynamic scoring engine that calculates operational risk and agent trust in real-time. By separating semantic meaning from execution and infrastructure, this framework establishes a foundational layer for sovereign, legally compliant, and monetizable machine logic.
CIOS, Probabilistic Trust Model, Machine Logic, Onto-Protocol, AI Compliance, Sovereign AI, Autonomous Agents
CIOS, Probabilistic Trust Model, Machine Logic, Onto-Protocol, AI Compliance, Sovereign AI, Autonomous Agents
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
