MANCaLog: A Logic for Multi-Attribute Network Cascades (Technical Report)
Paulo Shakarian, Gerardo I. Simari, Robert Schroeder

TL;DR
MANCaLog is a logic-based formalism designed to model complex cascade processes in multi-attribute networks, capturing attributes, temporal dynamics, uncertainty, and competing cascades, with proven computational tractability.
Contribution
This paper introduces MANCaLog, a novel logic programming framework that satisfies seven key properties for modeling multi-attribute network cascades, filling a gap in existing formal methods.
Findings
MANCaLog can represent attributes, time, uncertainty, and non-monotonic diffusion.
Algorithms for minimal model computation are developed.
The formalism is applicable to real-world cascade scenarios.
Abstract
The modeling of cascade processes in multi-agent systems in the form of complex networks has in recent years become an important topic of study due to its many applications: the adoption of commercial products, spread of disease, the diffusion of an idea, etc. In this paper, we begin by identifying a desiderata of seven properties that a framework for modeling such processes should satisfy: the ability to represent attributes of both nodes and edges, an explicit representation of time, the ability to represent non-Markovian temporal relationships, representation of uncertain information, the ability to represent competing cascades, allowance of non-monotonic diffusion, and computational tractability. We then present the MANCaLog language, a formalism based on logic programming that satisfies all these desiderata, and focus on algorithms for finding minimal models (from which the outcome…
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Taxonomy
TopicsAdvanced Database Systems and Queries · Data Management and Algorithms · Logic, Reasoning, and Knowledge
