21 papers · ranked by Valyu relevance
Gary B. Smith, Vaishak Belle, Ronald P. A. Petrick
In many scenarios where robots or autonomous systems may be deployed, the capacity to infer and reason about the intentions of other agents can improve the performance or utility of the system. For example, a smart home or assisted living facility is better able to select assistive services to deploy if it understands…
Kashif Mehmood, Katina Kralevska, David A. Palma
—Intent-based networking (IBN) facilitates the representation of consumer expectations in a declarative and domain-independent form. However, mapping intents to service and resource models remains an open challenge. IBN requires handling existing system data in a structured yet flexible structure way. Knowledge graphs…
Siamak Farshidi, Kiyan Rezaee, Sara Mazaheri, Amir Hossein Rahimi + 4 more
'Ali Dadashzadeh' 'Morteza Ziabakhsh' 'Sadegh Eskandari' 'Slinger Jansen'] Context: User intent modeling is a crucial process in Natural Language Processing that aims to identify the underlying purpose behind a user's request, enabling personalized responses. With a vast array of approaches introduced in the literature…
Kristina Dzeparoska, Jieyu Lin, Ali Tizghadam, Alberto Leon‐Garcia
—Automated management requires decomposing high-level user requests, such as intents, to an abstraction that the system can understand and execute. This is challenging because even a simple intent requires performing a number of ordered steps. And the task of identifying and adapting these steps (as conditions change)…
Trisha Mittal, Sanjoy Chowdhury, Pooja Guhan, Snikitha Chelluri + 1 more
'Dinesh Manocha'] Increasing use of social media has resulted in many detrimental effects in youth. With very little control over multimodal content consumed on these platforms and the false narratives conveyed by these multimodal social media postings, such platforms often impact the mental well-being of the users. To…
Lin Zhao, Ning Luan, Weihua Cheng, Shuming Feng + 4 more
In the field of electrical power material management, it is paramount that users receive accurate recommendations regarding the electrical power materials they require. Recently, a growing number of studies have been dedicated to graph neural network (GNN)-based recommendation systems due to their ability to seamlessly…
Iqbal H. Sarker
Artificial intelligence (AI) is a leading technology of the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR), with the capability of incorporating human behavior and intelligence into machines or systems. Thus, AI-based modeling is the key to build automated, intelligent, and smart systems…
Sara Zuppiroli, Carmelo Fabio Longo, Anna Sofia Lippolis, Rocco Paolillo + 5 more
The Belief-Desire-Intention (BDI) model is a cornerstone for representing rational agency in artificial intelligence and cognitive sciences. Yet, its integration into structured, semantically interoperable knowledge representations remains limited. This paper presents a formal BDI Ontology, conceived as a modular…
June-Woo Kim, Hyekyung Yoon, Ho-Young Jung, Christoph M. Friedrich
Successful applications of deep learning technologies in the natural language processing domain have improved text-based intent classifications. However, in practical spoken dialogue applications, the users’ articulation styles and background noises cause automatic speech recognition (ASR) errors, and these may lead…
Yiming Liu, Dorian Verdel, Raz Leib, Etienne Burdet + 1 more
Humans often collaborate under asymmetric information, for example when two people carry a table and only one knows the destination. They coordinate without speech using cues from movement kinematics, interaction forces, and object states. Characterizing this sensorimotor communication is difficult because these…
Cristina Gena
User modeling has traditionally relied on inferring preferences, traits, or intents from observable behaviour. While effective in many adaptive systems, this paradigm treats behaviour as the primary object of modeling and leaves mental-state attribution implicit. This assumption becomes limiting in socially situated…
Suyog Chandramouli, Danqing Shi, Aini Putkonen, Sebastiaan De Peuter + 4 more
Computational rationality explains human behavior as arising due to the maximization of expected utility under the constraints imposed by the environment and limited cognitive resources. This simple assumption, when instantiated via partially observable Markov decision processes (POMDPs), gives rise to a powerful…
Giorgio L. Manenti, Sepideh Khoneiveh, Jan Gläscher
Theory of Mind (ToM) refers to the ability to infer another agent’s latent mental states, such as intentions, beliefs, and strategies, to predict their behavior. A core feature of ToM is its recursive structure: individuals reason not only about what others think, but also about what others think about them. Existing…
Yasmine Ahmed, Cheryl A. Telmer, Gaoxiang Zhou, Natasa Miskov-Zivanov
New discoveries and knowledge are summarized in thousands of published papers per year per scientific domain, making it incomprehensible for scientists to account for all available knowledge relevant for their studies. In this paper, we present ACCORDION (ACCelerating and Optimizing model RecommenDatIONs), a novel…
Chenxi Wang, Jihui Zhao, Jingjing Zheng, Barak Raveh + 2 more
Developing and optimizing models for complex systems poses challenges due to the inherent complexity introduced by multiple types of input information and sources of uncertainty. In this study, we utilize Bayesian formalism to analytically examine the propagation of probability in the modeling process and propose…
Authors not listed
Digital twins are virtual companions for the design, scale-up, and control of chemical processes. Equipping digital twins with mechanistic models of their mirrored unit operation expands their range of applicability compared to pure data-driven models. As constructing mechanistic models requires time, effort, and…
J.M. Barnby, V. Bell, Q. Deeley, M. Mehta + 1 more
Striatal dopamine is important to paranoid attributions, although its computational role in social inference remains elusive. We employed a simple game theoretic paradigm and a formal Bayesian model of intentional attributions to investigate dopamine D2/D3 antagonism on ongoing mental state inference following joint…
Jeanette A.I. Johnson, Genevieve L. Stein-O’Brien, Max Booth, Randy Heiland + 31 more
Cells are fundamental units of life, constantly interacting and evolving as dynamical systems. While recent spatial multi-omics can quantitate individual cells’ characteristics and regulatory programs, forecasting their evolution ultimately requires mathematical modeling. We develop a conceptual framework—a cell…
Bryan Glazer, Jonathan Lifferth, Carlos F. Lopez
Many important processes in biology, such as signaling and gene regulation, can be described using logic models. These logic models are typically built to behaviorally emulate experimentally observed phenotypes, which are assumed to be steady states of a biological system. Most models are built by hand and therefore…
Authors not listed
Deriving versatile and robust mechanistic models from experimental data is a key challenge in engineering and natural sciences. This is especially true in chemical reaction engineering, where reactor manufacturers and operators increasingly pursue the development and maintenance of digital twins that rely on frequent…
Marius-Constantin Ilau, Tristan Caulfield, David Pym
The nature of information security has been, and probably will continue to be, marked by the asymmetric competition of attackers and defenders over the control of an uncertain environment. The reduction of this degree of uncertainty via an increase in understanding of that environment is a primary objective for both…