How can we efficiently determine meta-parameter values for deep learning-based time-series forecasting given a time-series dataset? This paper introduces Xtune, an efficient and novel meta-parameter tuning method for deep learning-based …

Although there are several systems that successfully generate construction steps for ruler and compass construction problems, none of them provides readable synthetic correctness proofs for generated constructions. In this paper, we demonstrate …

In this paper, we consider automated solving of triangle straightedge-and-compass construction problems by reducing them to automated planning. We consider the problems from the Wernick’s list, where each problem assumes that locations of three …

A strongly possible constraint is an intermediate concept between possible and certain constraints, based on the strongly possible world approach (a strongly possible world is obtained by replacing NULL’s by a value from the ones appearing in the …

The AGM paradigm, introduced by Alchourrón, Gärdenfors and Makinson, is a well-established formal framework that identifies the postulates (principles) governing any rational revision operator on belief sets. A central pillar in the study of …

We propose a formal model of a knowledge graph (abbr. KG) that classifies the ground triples into sets that correspond to the triple types. The triple types are partially ordered by the sub-type relation. Consequently, the sets of ground triples …

Many modern-day systems rely on information that is constantly arriving, and they need to make decisions based on it – a problem known as continuous query answering. In many situations, these systems can benefit from identifying possible outcomes …

Non-Intrusive Load Monitoring (NILM), also referred to as energy disaggregation, is the task of estimating a device level energy consumption using the aggregated energy consumption of different devices at one single measurement point without …

An attack graph is a concise portrayal of the various paths within an open system that enable an attacker to reach a prohibited state (such as gaining access to a restricted resource), despite the system’s preventive measures. The assessment of …

At the ADG 2023 a protocol, implemented on an extension of Larus automated theorem prover, to automatically complete statements and proofs in Euclidean geometry, was presented by S. T. Gonzalez, P. Janičić, and J. Narboux. The approach is …

In this paper, a novel method is presented to increase the developability of the quasi-developable Bézier surface from two design curves using the Simulated Annealing-based Shape Parameter Search (SASPS) algorithm based on the shape parameters of …

Robustness is a crucial requirement for the deployment of AI systems in real-world scenarios. In the context of AI planning, the concept of action reversibility, i.e., the ability to undo the effects of an action using a reverse plan, is a …

This paper presents a performance evaluation of several heuristic search algorithms in the context of pathfinding. Our objective is to assess the performance of these algorithms in various grid-based environments to present how specific domain …

Interactive reinforcement learning is an effective way to train agents via human feedback. However, it often requires the trainer (a human who provides feedback to the agent) to know the correct action for the agent. If the trainer is not always …

In this work, we study applications of the Conformal Prediction machine learning framework to the questions of statistical data testing. This technique is also known as Conformal Test Martingales. Earlier works on this topic used it to detect …

Ensuring the safe and effective operation of autonomous systems is a complex undertaking that inherently relies on underlying decision-making processes. To rigorously analyze these processes, formal verification methods, such as model checking …