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CP-nets-based user preference learning in automated negotiation through completion and correction
User preference learning is an important process in automated negotiation, because only when the negotiating agents are able to fully grasp the user...
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An extended knowledge compilation map for conditional preference statements-based and generalized additive utilities-based languages
Conditional preference statements have been used to compactly represent preferences over combinatorial domains. They are at the core of CP-nets and...
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CP-Nets, \(\pi \) -pref Nets, and Pareto Dominance
Two approaches have been proposed for the graphical handling of qualitative conditional preferences between solutions described in terms of a finite...
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Constructing CP-Nets from Users Past Selection
Although recommender systems have been significantly developed for providing customized services to users in various domains, they still have some...
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Deep-learning for automated markerless tracking of infants general movements
The presence of abnormal infant General Movements (GMs) is a strong predictor of progressive neurodevelopmental disorders, including cerebral palsy...
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Integrating CP-Nets in Reactive BDI Agents
Computational agents based upon the belief-desire-intention (BDI) architecture generally use reactive rules to trigger the execution of plans. For...
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Aggregating Preferences Represented by Conditional Preference Networks
This paper focuses on the task of aggregating preference orders over combinatorial domains, where both the individual and the aggregate preference...
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Petri Net Classes for Collaboration Mining: Assessment and Design Guidelines
Collaboration mining develops discovery, conformance checking, and enhancement techniques for collaboration processes. The collaboration process...
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From Identities to Quantities: Introducing Items and Decoupling Points to Object-Centric Process Mining
Logistics processes ensure that the right product is at the right location at the right time in the right quantity. Their efficiency is crucial to...
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Searching for Deviations in Trading Systems: Combining Control-Flow and Data Perspectives
Trading systems are software platforms that support the exchange of securities (e.g., company shares) between participants. In this paper, we present...
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CPMetric: Deep Siamese Networks for Metric Learning on Structured Preferences
Preferences are central to decision making by both machines and humans. Representing, learning, and reasoning with preferences is an important area...
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A Modular Framework for Modelling and Verification of Activities in Ambient Intelligent Systems
There is a growing need to introduce and develop formal techniques for computational models capable of faithfully modelling systems of high...
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Object-Centric Process Mining: An Introduction
Initially, the focus of process mining was on processes evolving around a single type of objects, e.g., orders, order lines, payments, deliveries, or...
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End-to-end data-dependent routing in multi-path neural networks
Neural networks are known to give better performance with increased depth due to their ability to learn more abstract features. Although the...
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Optimizing performance of serverless application using PanOpticon
Serverless computing is popular due to its pay-as-you-go price, high availability, high scalability, and less resource management strain. When moving...
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TendiffPure: a convolutional tensor-train denoising diffusion model for purification
Diffusion models are effective purification methods, where the noises or adversarial attacks are removed using generative approaches before...
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A Geometric Theory for Binary Classification of Finite Datasets by DNNs with Relu Activations
In this paper we investigate deep neural networks for binary classification of datasets from geometric perspective in order to understand the working...
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Energy-aware dynamic response and efficient consolidation strategies for disaster survivability of cloud microservices architecture
Computer system resilience refers to the ability of a computer system to continue functioning even in the face of unexpected events or disruptions....
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Distributed Synthesis of Asynchronously Communicating Distributed Process Models
We investigate to what extent existing algorithms for the discovery of component models from event logs can be leveraged to a system of...
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Possibilistic Preference Networks and Lexicographic Preference Trees – A Comparison
The paper compares two graphical approaches proposed for the qualitative modeling of preferences:...