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Generative Logic Model for Data-Driven Discovery of Symbolic Commonsense Knowledge

   Cardiff School of Computer Science & Informatics

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  Dr Hiroyuki Kido  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

This project aims to study and implement algorithms for generating symbolic commonsense knowledge from potentially inconsistent, incomplete, dynamic, subjective and distributed data. The project uses a generative logic model, which is a data-driven logical and statistical reasoning approach taking advantage of the expressive power of formal logic and the predictive power of Bayesian machine learning. Target applications of the project include argumentation mining, explainable artificial intelligence, counterfactuals and causal inference. The deliverables include the dissertation and algorithm source code. The project will expose the successful student to the interdisciplinary field across logic, machine learning and neuroscience, where important open questions remain unsolved. Under the research outline, the project will provide the successful student with the opportunity to follow their curiosity and to carry out research into something they are interested in.

Contact for information on the project: [Email Address Removed]

Keywords: Logic, reasoning, learning, Bayesian statistics, prediction, explanation, entailment, paraconsistency, counterfactuals, nonmonotonicity, action, argumentation, data mining

Academic criteria: A 2:1 Honours undergraduate degree or a master's degree, in computing or a related subject. Applicants with appropriate professional experience are also considered. Degree-level mathematics (or equivalent) is required for research in some project areas.

Applicants for whom English is not their first language must demonstrate proficiency by obtaining an IELTS score of at least 6.5 overall, with a minimum of 6.0 in each skills component.

How to apply:

How to apply:

Please contact the supervisors of the project prior to submitting your application to discuss and develop an individual research proposal that builds on the information provided in this advert. Once you have developed the proposal with support from the supervisors, please submit your application following the instructions provided below

Please submit your application before the application deadline 29th April 2022 via Computer Science and Informatics - Study - Cardiff University

In order to be considered candidates must submit the following information: 

  • Supporting statement 
  • CV 
  • In the ‘Research Proposal’ section of the application enter the name of the project you are applying to and upload your Individual research proposal, as mentioned above in BOLD
  • In the funding field of your application, insert “I am applying for 2022 PhD Scholarship in Computer Science and Informatics”, and specify the project title and supervisors of this project in the text box provided.
  • Qualification certificates and Transcripts
  • References x 2 
  • Proof of English language (if applicable)

Interview - If the application meets the entrance requirements, you will be invited to an interview

If you have any questions or need more information, please contact [Email Address Removed]

Funding Notes

A School-Funded PhD Scholarship is available for entry 2022/23.
In the Funding field of your application, insert "I am applying for 2022 PhD Scholarship" and specify the project title and supervisor of this project in the fields provided.
This project is also open to Self-Funded students worldwide. If you are interested in applying for a Self-Funded PhD, please search FindAPhD for this specific project title, supervisor or School within its Scholarships category.


Hiroyuki Kido, Keishi Okamoto: Bayes Meets Entailment and Prediction: Commonsense Reasoning with Non-monotonicity, Paraconsistency and Predictive Accuracy. CoRR abs/2012.08479v3 (2020)
Hiroyuki Kido: Bayesian Entailment Hypothesis: How Brains Implement Monotonic and Non-monotonic Reasoning. CoRR abs/2005.00961 (2020)

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