Dyadic Deontic Logic in HOL : Faithful Embedding and Meta-Theoretical Experiments

A shallow semantical embedding of a dyadic deontic logic by Carmo and Jones in classical higher-order logic is presented. The embedding is proven sound and complete, that is, faithful. This result provides the theoretical foundation for the implementation and automation of dyadic deontic logic within off-the-shelf higher-order theorem provers and proof assistants. To demonstrate the practical relevance of our contribution, the embedding has been encoded in the Isabelle/HOL proof assistant. As a result a sound and complete (interactive and automated) theorem prover for the dyadic deontic logic of Carmo and Jones has been obtained. Experiments have been conducted which illustrate how the exploration and assessment of meta-theoretical properties of the embedded logic can be supported with automated reasoning tools integrated with Isabelle/HOL

Faithful Semantical Embedding of a Dyadic Deontic Logic in HOL

A shallow semantical embedding of a dyadic deontic logic by Carmo and Jones in classical higher-order logic is presented. This embedding is proven sound and complete, that is, faithful. The work presented here provides the theoretical foundation for the implementation and automation of dyadic deontic logic within off-the-shelf higher-order theorem provers and proof assistants.Comment: 23 pages, 3 figure

Implementation of Dyadic Deontic Logic E in Isabelle/HOL

We have devised a shallow semantical embedding of a dyadic deontic logic (by B.Hansson and \AA{}qvist) in classical higher-order logic. This embedding has been encoded in Isabelle/HOL, which turns this system into a proof assistant for deontic logic reasoning. The experiments with this environment provide evidence that this logic \textit{implementation} fruitfully enables interactive and automated reasoning at the meta-level and the object-level

Faithful Semantical Embedding of a Dyadic Deontic Logic in HOL

A shallow semantical embedding of a dyadic deontic logic by Carmo and Jones in classical higher-order logic is presented. This embedding is proven sound and complete, that is, faithful. The work presented here provides the theoretical foundation for the implementation and automation of dyadic deontic logic within off-the-shelf higher-order theorem provers and proof assistants

A Dyadic Deontic Logic in HOL

A shallow semantical embedding of a dyadic deontic logic by Carmo and Jones in classical higher-order logic is presented. This embedding is proven sound and complete, that is, faithful. The work presented here provides the theoretical foundation for the implementation and automation of dyadic deontic logic within off-the-shelf higher-order theorem provers and proof assistants

Emulating the Human Mind: A Neural-symbolic Link Prediction Model with Fast and Slow Reasoning and Filtered Rules

Link prediction is an important task in addressing the incompleteness problem of knowledge graphs (KG). Previous link prediction models suffer from issues related to either performance or explanatory capability. Furthermore, models that are capable of generating explanations, often struggle with erroneous paths or reasoning leading to the correct answer. To address these challenges, we introduce a novel Neural-Symbolic model named FaSt-FLiP (stands for Fast and Slow Thinking with Filtered rules for Link Prediction task), inspired by two distinct aspects of human cognition: "commonsense reasoning" and "thinking, fast and slow." Our objective is to combine a logical and neural model for enhanced link prediction. To tackle the challenge of dealing with incorrect paths or rules generated by the logical model, we propose a semi-supervised method to convert rules into sentences. These sentences are then subjected to assessment and removal of incorrect rules using an NLI (Natural Language Inference) model. Our approach to combining logical and neural models involves first obtaining answers from both the logical and neural models. These answers are subsequently unified using an Inference Engine module, which has been realized through both algorithmic implementation and a novel neural model architecture. To validate the efficacy of our model, we conducted a series of experiments. The results demonstrate the superior performance of our model in both link prediction metrics and the generation of more reliable explanations

I/O Logic in HOL

A shallow semantical embedding of Input/Output logic in classical higher-order logic is presented, and shown to be faithful (sound an complete). This embedding has been implemented in the higher-order proof assistant Isabelle/HOL. We provide an empirical regulative framework for assessing General Data Protection Regulation

Microelectronics-Based Biosensors Dedicated to the Detection of Neurotransmitters: A Review

Dysregulation of neurotransmitters (NTs) in the human body are related to diseases such as Parkinson's and Alzheimer's. The mechanisms of several neurological disorders, such as epilepsy, have been linked to NTs. Because the number of diagnosed cases is increasing, the diagnosis and treatment of such diseases are important. To detect biomolecules including NTs, microtechnology, micro and nanoelectronics have become popular in the form of the miniaturization of medical and clinical devices. They offer high-performance features in terms of sensitivity, as well as low-background noise. In this paper, we review various devices and circuit techniques used for monitoring NTs in vitro and in vivo and compare various methods described in recent publications