Temporal and Relational Models for Causality
Author | : Katerina Marazopoulou |
Publisher | : |
Total Pages | : |
Release | : 2017 |
ISBN-10 | : OCLC:1015220875 |
ISBN-13 | : |
Rating | : 4/5 ( Downloads) |
Download or read book Temporal and Relational Models for Causality written by Katerina Marazopoulou and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Discovering causal dependence is central to understanding the behavior of complex systems and to selecting actions that will achieve particular outcomes. The majority of work in this area has focused on propositional domains, where data instances are assumed to be independent and identically distributed (i.i.d.). However, many real-world domains are inherently relational, i.e., they consist of multiple types of entities that interact with each other, and temporal, i.e., they change over time. This thesis focuses on causal modeling for these more complex relational and temporal domains. This thesis provides an in-depth investigation of the properties of relational models and is extending their expressivity to include a temporal dimension. Specifically, we first investigate alternative ways to ground relational models, and we provide an in-depth analysis of the impact of alternative grounding semantics for feature construction, causal effect estimation, and model selection. Then, we extend relational models to represent discrete time. We generalize the theory of d-separation for this class of temporal and relational models. Finally, we provide a constraint-based algorithm, TRCD, to learn the structure of temporal relational models from data.