Open Early Stage Researcher/PhD Position in Artificial Intelligence: Explaining Logical Formulas

One ESR PhD position in Artificial Intelligence within the framework of NL4XAI: Interactive Natural Language Technology for Explainable Artificial Intelligence, a project funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 860621.



NL4XAI is a European Training Network (ETN) project, which will train 11 creative, entrepreneurial and innovative early-stage researchers (ESRs), who will face the challenge of making Artificial Intelligence (AI) self-explanatory and thus contribute to translating knowledge into products and services for economic and social benefit, with the support of Explainable AI (XAI) systems.

The focus of NL4XAI is in the automatic generation of interactive explanations in natural language, just as humans naturally do, and as a complement to visualization tools. As a result, ESRs are expected to leverage the usage of AI models and techniques even by non-expert users.

Reference number: NL4XAI- ESR2

PhD research topic: From grey-box models to explainable models

Objectives: To define, design, develop and implement an agnostic-based approach for providing Natural Language explanations of Bayesian Networks reasoning using a linguistic imprecise knowledge representation and reasoning method. Taking as a starting point the interpretation of Bayesian variables, values and probability functions as imprecise quantified statements, the Bayesian reasoning process will be modelled as a quantified syllogism, which can be solved as a mathematical programming problem. The target is to propose, test and validate models for explaining in Natural Language different reasoning schemes, such as predictive, diagnostic or inter-causal, with an efficient implementation for addressing scalability problems which may occur in large Bayesian Networks. The explanation models will be based both in the agnostic-based approach herein considered as well as in the results of ESR3.


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Deadline for applications is June 4, 2021, at 23h59 CET (UCT + 01:00)

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