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By the ubiquitous usage of machine learning models with their inherent black-box nature, the necessity of explaining the decisions made by these models has become crucial. Although outcome explanation has been recently taken into account as a ...

In this paper we sketch a vision of explainability of intelligent systems as a logic approach suitable to be injected into and exploited by the system actors once integrated with sub-symbolic techniques.

In particular, we show how argumentation ...

Pneumonia has been recognized as a common and potentially lethal condition for nearly two centuries. The COVID-19 disease caused by the SARS-CoV-2 virus first appeared in Wuhan, China, and is considered a serious disease due to its high ...

The interest in Explainable Artificial Intelligence (XAI) research is dramatically grown during the last few years. The main reason is the need of having systems that beyond being effective are also able to describe how a certain output has been ...

Learning and training processes are starting to be affected by the diffusion of Artificial Intelligence (AI) techniques and methods. AI can be variously exploited for supporting education, though especially deep learning (DL) models are normally ...

Many practically relevant computing artifacts are forms of graphs, as, e.g., neural networks, mathematical expressions, finite automata. This great generality of the graph abstraction makes it desirable a way for searching in the space of graphs ...

Hybrid algorithms are powerful search algorithms obtained by the combination of metaheuristics with other optimization techniques, although the most common hybridization is to apply a local solver method within evolutionary computation algorithms. ...

In this paper we introduce $\mathsf{AASExts}$, an algorithm for computing semi–stable extensions. We improve techniques developed for other semantics, notably preferred semantics, as well as leverage recent advances in All-SAT community. We prove our ...

In its original definition, the Abstract Argumentation framework considers atomic claims and a binary attack relationship among them, based on which different semantics would select subsets of claims consistently supporting the same position in a ...

While agent-based modelling languages naturally implement concurrency, the currently available languages for argumentation do not allow to explicitly model this type of interaction. In this paper we introduce a concurrent language for handling ...

The development and integration of fault-tolerant systems has considerably increased flight safety over the years. One of the research areas that has made this improvement possible is the development of more advanced flight guidance systems, that ...

Design patterns are widely used in various areas of computer science, the most notable example being software engineering. They have been introduced also for supporting the encoding of automated planning knowledge models, but up till now, with ...

The optimization of daily operating room surgery schedule can be problematic because of many constraints, like to determine the starting time of different surgeries and allocating the required resources, including the availability of surgical ...

We present theoretical and numerical results concerning the problem to find the path that minimizes the time to navigate between two given points in a complex fluid under realistic navigation constraints. We contrast deterministic Optimal ...

This paper presents different methodologies to enhance the human-robot interaction during the control of brain-machine interface (BMI) driven telepresence robots. To overcome the limitations of BMIs, namely the low bit rate and the intrinsic ...

Social robots and artificial agents should be able to interact with the user in the most natural way possible. This work describes the basic principles of a conversation system designed for social robots and artificial agents, which relies on ...

We focus on visually grounded dialogue history encoding. We show that GuessWhat?! can be used as a “diagnostic” dataset to understand whether State-of-the-Art encoders manage to capture salient information in the dialogue history. We compare ...

Natural language programming (NLPr) allows people to program in natural language (NL) for specific domains. It poses great potential since it gives non-experts the ability to develop projects without exhaustive training. However, complex ...

A basic technique used in algorithms for constraint satisfaction problems (CSPs) is removing values that are locally inconsistent, since they cannot form part of a globally consistent solution. The best-known algorithms of this type establish arc ...

The Traveling Salesperson Problem (TSP) is a well-known problem addressed in the literature through various techniques, including Integer Linear Programming, Constraint Programming (CP) and Local Search. Many real life instances belong to the ...

Explanations of Machine Learning (ML) models often address a [inline-graphic not available: see fulltext] question. Such explanations can be related with selecting feature-value pairs which are sufficient for the prediction. Recent work has ...