Causal-Temporal Event Graphs: A Formal Model for Recursive Agent Execution Traces
Simon Foldvik

TL;DR
This paper introduces causal-temporal event graphs (CTEGs) as a formal model for recursive agent execution traces, capturing causal and temporal relationships with potential applications in verification and data management.
Contribution
It formalizes CTEGs as a recursive hierarchy of finite, well-structured execution traces with properties supporting compositionality, robustness, and cryptographic verification.
Findings
CTEGs form a hierarchy converging at a least fixed point.
Stabilization occurs at the first level if subagent traces are opaque.
Supports compositional, tamper-evident, and database-compatible execution modeling.
Abstract
We introduce causal-temporal event graphs (CTEGs) as a formal model for fully resolved recursive agent execution records under single-parenthood causal semantics. We formalise direct event emissions and recursive subagent invocations as extension procedures on generic typed temporal graphs and show that the recursive closure of the induced maximal dynamics starting from single causal roots consists entirely of finite sequences of CTEGs. A CTEG is a rooted arborescence whose nodes carry timestamps and event types, subject to the constraint that timestamps be strictly increasing along causal paths. We realise as the increasing union of a recursive hierarchy of agent execution levels parametrised by recursion depth, which is recognised as the ascending Kleene chain of a monotone operator…
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