bluuebunny/crossref_metadata_2025 huggingface dataset:
Pipelining Argumentation Technologies
Authors: Snaith Mark  , Devereux Joseph  , Lawrence John  , Reed Chris
Published: February 2025

Software tools for working with argument generally exist as large systems that wrap their entire feature set in the application as a whole. This approach, while perfectly valid, can result in users having to use small parts of multiple systems to carry out a specific task. In this paper, we present a series of web services, that each encapsulate small pieces of functionality for working with argument. We then demonstrate two example systems built by connecting these services in the form of a UNIX-style pipeline.
Moving Intervals for Nonlinear Time Series Forecasting
Authors: Sánchez Germán  , Samà Albert  , Ruiz Francisco J.  , Agell Núria
Published: February 2025

In this paper a new forecasting methodology to be used on time series prediction is introduced. The considered nonlinear method is based on support vector machines (SVM) using an interval kernel. An extended intersection kernel is introduced to discriminate between disjoint intervals in reference to the existing distance among them. The model presented is applied to forecast exchange ratios using six world's major currencies. The results obtained show that SVMs based on interval kernel have a similar behavior than other SVM classical forecasting approaches, allowing its performance to be seen as very promising when using high frequency data.
Assessing the Role of Metacognition in GMU BICA
Authors: Kalish Michael Q.  , Samsonovich Alexei V.  , Coletti Mark A.  , De Jong Kenneth A.
Published: February 2025

GMU BICA is a biologically inspired cognitive architecture developed at George Mason University. Its main distinguishing feature is a system of data structures called “mental states” that enables various forms of metacognition. The present study develops an understanding of the role of metacognition during working scenario generation (a general element of the cognitive cycle in GMU BICA). This is done by a computational experiment with a rapid prototype of the architecture that generates metacognitive mental states. A spatial learning / spatial navigation paradigm is used here, with a virtual robot implemented in CASTLE. Results show a significant increase in both behavioral and cognitive efficiency of the agent when metacognition is turned on. Generalizations are discussed.
Confluent Term Rewriting for Only-knowing Logics
Authors: Lian Espen H.  , Johnsen Einar Broch  , Waaler Arild
Published: February 2025

Combining term rewriting and modal logics, this paper addresses confluence and termination of rewrite systems introduced for only-knowing logics. The rewrite systems contain a rule scheme that gives rise to an infinite number of critical pairs, hence we cannot check the joinability of every critical pair directly, in order to establish local confluence. We investigate conditions that are sufficient for confluence and identify a set of rewrite rules that satisfy these conditions; however, the general confluence result makes it easier to check confluence also of stronger systems should one want additional rules. The results provide a firm logical basis for implementation of procedures that compute autoepistemic expansions.
A Workbench for Anytime Reasoning by Ontology Approximation
Authors: Tagni Gaston  , Schlobach Stefan  , ten Teije Annette  , van Harmelen Frank  , Karafotias Giorgios
Published: February 2025

Reasoning is computationally expensive. This is especially true for reasoning on the Web, where data sets are very large and often described by complex terminologies. One way to reduce this complexity is through the use of approximate reasoning methods which trade one computational property (eg. quality of answers) for others, such as time and memory. Previous research into approximation on the Semantic Web has been rather ad-hoc, and we propose a framework for systematically studying such methods. We developed a workbench which allows the structured combination of different algorithms for approximation, reasoning and measuring in one single framework. As a case-study we investigate an incremental method for instance retrieval through ontology approximation, and we use our workbench to study the computational behaviour of several approximation strategies.
Argumentation with Value Judgments
Authors: Grabmair Matthias  , Ashley Kevin D.
Published: February 2025

This paper presents a formalism modeling legal reasoning with fact patterns and their substantive effects on legal values. It centers on the concept of a value judgment, i.e. a determination that one factual situation is preferable over another by virtue of their respective effects on values. This allows the modeling of legal sources as sets of value judgments and legal methodologies as collections of argumentation schemes. The paper briefly derives the formalism from legal theory and elaborates on its use in the context of an example of hypothetical reasoning.
Balancing of Legal Principles and Constraint Satisfaction
Authors: Araszkiewicz Michał
Published: February 2025

Robert Alexy is one of the main advocates of the so-called Rules and Principles Theory (hereafter: RPT). According to the RPT, legal norms can be divided into legal rules and legal principles. One of the main criteria for this distinction is - Alexy argues - that legal rules are applied by means of the Subsumption Formula, while legal principles - by means of the so-called Weight Formula (hereafter: WF). The WF offers an important insight into the structure of the process of balancing in legal reasoning. Alexy's proposal leads to many doubts and questions, however. The aim of the paper is to examine the appropriateness of the WF and the problem of balancing in legal reasoning from the perspective inspired by the constraint satisfaction theory of coherence, developed by Paul Thagard. My claim is that this theory enables us to elucidate many problematic features of the WF and to recast the structure of legal balancing in more transparent and efficient manner. The existing workable algorithms designed for computing other kinds of coherence-based reasoning (for instance, explanatory reasoning or analogical reasoning), make possible to adopt the programs employing these algorithms for computation of coherence in balancing of principles. However, the analysis presented here is mainly conceptual and it has only preparatory character in relation with the possible computational implementations in the future.
A Kernel-level UNDO/REDO Mechanism for the Transformation-Driven Architecture
Authors: Kozlovics Sergejs  , Rencis Edgars  , Rikacovs Sergejs  , Cerans Karlis
Published: February 2025

The Transformation-Driven Architecture, TDA, is an approach for creating systems and tools. Can the UNDO/REDO functionality be easily (implicitly) introduced to the tools built upon TDA? The paper explains that this can be done at the level of TDA kernel in a universal way. We present the basic UNDO/REDO functionality as well as some its extensions.
A Geometrically Constrained ICA Algorithm for Blind Separation in Convolutive Environments
Authors: Scarpiniti Michele  , Di Palma Francesco  , Parisi Raffaele  , Uncini Aurelio
Published: February 2025

In this paper a blind source separation algorithm in convolutive environment is presented. In order to avoid the classical permutation ambiguity in the frequency domain solution, a geometrical constraint is considered. Moreover a beam-former algorithm is integrated with the proposed solution: in this way the directivity pattern of the proposed architecture can take into account the residual permutation at low frequencies and the scaling inconsistency. Several experimental results are shown to demonstrate the effectiveness of the proposed method.
Passive Black-Box Cryptanalysis of an Ultralightweight Protocol after Eavesdropping One Authentication Session
Authors: Hernandez-Castro Julio Cesar  , Peris-Lopez Pedro  , Tapiador Juan E.  , Phan Raphael C.-W.  , Li Tieyan
Published: February 2025

We present a black-box attack that is able to fully recover the secret values shared between entities involved in an authentication protocol. First, we explain how this black-box technique can be successfully applied against the class of protocols commonly known as ultralightweight protocols. Then, the effectiveness of this attack is shown by successfully cryptanalyzing the David-Prasad ultralightweight protocol [1], which is one of the most recent proposals in this research area. We show how we can recover the secret static identifier ID – the most valuable information which the protocol is designed to conceal – after eavesdropping only one protocol session. Our attack compares favorably to previous attacks against this protocol, and constitutes an interesting alternative for the very realistic scenario of attackers having access only to messages exchanged during a single authentication session. We also show how this disclosure attack can be used to mount a very powerful traceability attack that also improves on previous results.
Innovations in Metropolitan Governance in South Asian Countries
Authors: Khan Mohammad Mohabbat
Published: February 2025

Metropolitan governments in South Asia are facing difficult challenges in meeting citizens' demands for better services. Innovations are being attempted to effectively counter the challenges faced and to prepare to move forward into an uncertain future. Innovations have been more successfully implemented and institutionalized in some Indian cities, but slow to come in two Pakistani cities. The experience of Colombo in Sri Lanka has been encouraging from the perspective of innovation initiation and institutionalization. Dhaka's experience in Bangladesh provides a mixed picture as small innovations are initiated from time to time but these have not been institutionalized. The variables critical for the successful introduction and sustenance of innovations in metropolitan governance are: active citizen involvement, dissemination of relevant information to citizens, regular monitoring of the progress of innovations through client participation, transparency in the decision-making process and accountability of the officials concerned to the consumers of service.
Innovation for Constrained Municipalities: The Transformation of Japanese Local Government under Central Government Pressure
Authors: Mori Hiroyuki
Published: February 2025

This chapter analyzes the change in local governance with regard to the financial crisis in Japan. The Japanese system of public administration is based on a multilayered structure, which may increase efficiency but it is nevertheless severely constrained by the financial difficulties of local governments. Such a condition is likely to cause the underutilization of the innovation potential of local governments. What should be done to improve the situation is to recover the tax system, promote innovation in local public governance, and fix the existing intergovernmental fiscal relations by emphasizing the role of local government initiatives. The latter are essential to the attainment of the goal of creating high performance of local government in Japan.
Perspectives on artificial intelligence in a business environment
Authors: Nordin Peter
Published: February 2025

This lecture will give three perspectives on artificial intelligence in a business environment: Some notes from a personal journey having created a dozen successful AI companies in Scandinavia. A collection of conclusions and observations hopefully valuable for anyone interested in turning their research into a commercial venture with a focus on how the Scandinavian market works. And finally an overview of the “lowest-hanging fruit” and biggest success stories of commercial AI at present.
On the Lower Bounds for Asymmetrical Insertion-deletion Languages
Authors: Bel-Enguix Gemma  , Krassovitskiy Alexander  , Rogozhin Yurii  , Verlan Sergey
Published: February 2025

This article investigates languages generated by insertion-deletion systems of small size. Four classes of asymmetrical insertion-deletion systems are considered; two of them are known to be computationally uncomplete. We show a series of proper inclusions that permit to determine some non-trivial lower bounds for the corresponding languages.
Syntax-Semantics Interface for Lexical Inflection with the Language of Acyclic Recursion
Authors: Loukanova Roussanka
Published: February 2025

The paper introduces work on computational syntax-semantics interface in lexicon for verbal inflection. It uses syntactic theory in the approach of Constraint-Based Lexicalist Grammar (CBLG). Semantic representations are renderings by Moschovakis' formal language of acyclic recursion.
Evaluating an Emergent Behaviour Algorithm in JCSP for Energy Conservation in Lighting Systems
Authors: Kosek Anna  , Syed Aly  , Kerridge Jon
Published: February 2025

Since the invention of the light bulb, artificial light is accompanying people all around the world every day and night. As the light bulb itself evolved a lot through years, light control systems are still switch-based and require users to make most of the decisions about its behaviour. This paper presents an algorithm for emergent behaviour in a lighting system to achieve stable, user defined light level, while saving energy. The algorithm employs a parallel design and was tested using JCSP.
Serving Web Content with Dynamic Process Networks in Go
Authors: Whitehead II James
Published: February 2025

This paper introduces webpipes, a compositional web server toolkit written using the Go programming language as part of an investigation of concurrent software architectures. This toolkit utilizes an architecture where multiple functional components respond to requests, rather than the traditional monolithic web server model. We provide a classification of web server components and a set of type definitions based on these insights that make it easier for programmers to create new purpose-built components for their systems. The abstractions provided by our toolkit allow servers to be deployed using several concurrency strategies. We examine the overhead of such a framework, and discuss possible enhancements that may help to reduce this overhead.
8. Zinc Transporters
Authors: Cousins Robert J.  , Lichten Louis A.
Published: February 2025

Zinc transporters maintain zinc homeostasis in integrative systems through controlling absorption and excretion of this essential micronutrient as well as by regulating inter-organ and intracellular zinc for functional needs. Studies of the 24 zinc transporters derived from two families have relevance to both clinical science and basic science. These studies are necessary to address the questions of what transported zinc does and why multiple zinc transporters have evolved.
3. Nutritional Aspects of Zinc Consumption
Authors: Sandstead Harold H.
Published: February 2025

Zinc is most bioavailable from animal flesh, and red meat is the richest common source. In contrast, foods prepared from cereals, legumes, other seeds, and other plant parts may be rich in indigestible zinc-binding ligands, such as phytate and certain dietary fibers, that suppress zinc bioavailability. Zinc absorption from zinc supplements is modulated over time so that the amount of zinc absorbed does not exceed need. Supplements of calcium, iron and folate are reported to suppress zinc absorption under some circumstances. Treatment of zinc deficiency with zinc is most efficacious when other micronutrient are also available in adequate amounts.
15. Zinc in Pregnancy
Authors: Coyle Peter  , Cowley Carina  , Rofe Allan
Published: February 2025

The essentiality of zinc is highlighted in pregnancy where many fundamental processes are dependent on Zn. In addition to adequate intake during pregnancy and lactation, it is recognised that a range of pathological outcomes are associated with zinc deficiency including; birth defects, growth retardation, impaired immune function and increased susceptibility to infection, skin disorders and central nervous system dysfunction. Furthermore, our understanding of pregnancy outcomes has been advanced by the better understanding of mechanisms that underlie the altered supply of Zn to the fetus in response to the maternal exposure to toxins, infection and disease. The metal binding protein, metallothionein is important in altering Zn distribution following exposure to alcohol or infection.
21. Zinc and Alzheimer's Disease
Authors: Adlard Paul A.  , Bush Ashley I.
Published: February 2025

The maintenance of normal zinc levels is crucial to a variety of cellular functions, with zinc also shown to be a key mediator of a number of central and peripheral disorders. Within the brain, there is now mounting evidence for a pivotal role for zinc dyshomeostasis in the onset and pathological and symptomatic progression of Alzheimer's disease- the most common form of dementia. In this chapter we will discuss the evidence for a disturbance in zinc levels in both the brain and peripheral compartments in Alzheimer's disease. We will further outline the various cellular targets that may be affected by this and how it may contribute to the pathophysiology of Alzheimer's disease. Finally, we will discuss the notion that zinc dyshomeostasis may represent a therapeutic target for this progressive neurodegenerative disorder.
27. Zinc and Eye Diseases
Authors: Barzegar-Befroei Neda  , Cahyadi Sabrina  , Gango Ashraf  , Peto Tunde  , Lengyel Imre
Published: February 2025

The eye, especially the retina and the underlying retinal pigment epithelium/choroid complex, contain high concentrations of zinc. Therefore, it is not surprising that several eye disorders are associated with altered zinc balance, and zinc supplementation has become a choice of treatment for diseases like age-related macular degeneration. Despite its importance in health and diseases of the eye it is still not well understood how zinc participates in cellular and molecular events and how zinc supplementation might be beneficial.
A Flexible Modeling Approach for Supporting Rapid Business Simulations
Authors: Revetria Roberto  , Testa Alessandro  , Mosca Roberto  , Bertolotto Alessandro
Published: February 2025

The raise of BRICs countries has been regarded recently as an opportunity for cost reduction from western companies resulting in a pressure to increase of the delocalization of the production process with the consequence of increasing of the management complexity requiring specific ERP systems able to deal with new and improved process. Every company has business processes in order to manufacture products, to provide services, to purchase goods and even to maintain plants and company's assets; the basic of every change is the knowledge of the process and the understanding the possible evolution. In nowadays systems information systems and cloud infrastructures record events; these events can be used to make processes visible and thus a modeling framework may provide the insights necessary to manage, control, and improve processes. This paper present a general approach and a set of case studies where Computational Intelligence may assist the “self modeling” of complex processes.
Towards plant monitoring through Next Best View
Authors: Foix Sergi  , Alenyà Guillem  , Torras Carme
Published: February 2025

Monitoring plants using leaf feature detection is a challenging perception task because different leaves, even from the same plant, may have very different shapes, sizes and deformations. In addition, leaves may be occluded by other leaves making it hard to determine some of their characteristics. In this paper we use a Time-of-Flight (ToF) camera mounted on a robot arm to acquire the depth information needed for plant leaf detection. Under a Next Best View (NBV) paradigm, we propose a criterion to compute a new camera position that offers a better view of a target leaf. The proposed criterion exploits some typical errors of the ToF camera, which are common to other 3D sensing devices as well. This approach is also useful when more than one leaf is segmented as the same region, since moving the camera following the same NBV criterion helps to disambiguate this situation.
Mental Imagery in a Graphical Cognitive Architecture
Authors: Rosenbloom Paul S.
Published: February 2025

Can mental imagery be incorporated uniformly into a cognitive architecture by leveraging the mixed (relational and probabilistic) hybrid (discrete and continuous) processing supported by factor graphs? This article takes an initial step towards answering this question via an implementation in a graphical cognitive architecture of a version of the Eight Puzzle based on a hybrid function representation and a factor node optimized for object translation.
Neural Planning and Reasoning Using the Synaptic Connections of the Basal Ganglia and Thalamus
Authors: Stewart Terrence C.  , Eliasmith Chris
Published: February 2025

In previous work, we have shown how to construct biologically plausible models of a wide variety of cognitive tasks. This process involves converting algorithms into numerical vectors (represented by the spiking activity of a group of neurons) and operations on those vectors (implemented via synaptic connections between groups). We have used this technique to create a neural model capable of solving the Tower of Hanoi task, involving symbolic reasoning, planning, and goal retrieval. Constructing this neural cognitive model involved breaking the task down into sixteen general-purpose “rules” which can be implemented by specifying particular synaptic connections from the cortex to the basal ganglia, and from the thalamus back to the cortex. In this paper, we present a breakdown and discussion of these rules, showing how they differ from those found in traditional symbolic cognitive models. This leads to a novel method of constructing biologically realistic cognitive models with improved capabilities over classical production system models.
The role of the predicted present in artificial and natural cognitive systems
Authors: Diamond Alan  , Holland Owen  , Marques Hugo Gravato
Published: February 2025

In previous work, we have argued that a sophisticated cognitive system with a complex body must possess configurable models of itself (or at least its body) and the world, along with the necessary infrastructure to use the modelled interactions between these two components to select relatively advantageous actions. These models may be used to generate representations of the future (imagination) and the past (episodic memory). In this paper we will explore some problems surrounding the representation of the present arising from the use of such models in the artificial cognitive system under development within the ECCEROBOT project. There are two aspects to consider: the representation of the state of the robot's body within the self model, and the representation of the state of the external world within the world model. In both natural and robotic systems, the processing of the sensory data carrying state information takes a considerable time, and so any estimates of the present states of both the agent and the world would have to be obtained by using predictive models. However, it appears that there is no need for any such representations to be generated in the course of selecting a course of action using self and world models, since representations are only of the future or the past. This may call into question the utility and timing of the apparent perception of the present in humans.
Evaluating the Contribution of Top-Down Feedback and Post-Learning Reconstruction
Authors: Achler Tsvi  , Bettencourt Luís M.A.
Published: February 2025

Deep generative models and their associated top-down architecture are gaining popularity in neuroscience and computer vision. In this paper we link our previous work with regulatory feedback networks to generative models. We show that generative model's and regulatory feedback model's equations can share the same fixed points. Thus, phenomena observed using regulatory feedback can also apply to generative models. This suggests that generative models can also be developed to identify mixtures of patterns, address problems associated with binding, and display the ability to estimate numerosity.
ELM-based Algorithms for Nonstationary Volterra System Identification
Authors: Ye Yibin  , Squartini Stefano  , Piazza Francesco
Published: February 2025

Time-Varying Neural Network (TV-NN) is a novel structure applied to nonstationary system identification tasks. Up to date, there are two main categories of approaches to train TV-NN: Gradient-based and ELM-based. Among the latter, the variants EM-ELM-TV and EM-OB have been recently proposed by the authors to determine the number of hidden nodes and the number of output bases functions automatically, which are important parameters to be preset in standard ELM. The aim of this contribution consists in evaluating the performances of aforementioned ELM-based algorithms in training TV-NNs to identify nonstationary Volterra systems, which are used to model a wide category of nonstationary nonlinear systems. Simulation results show that with polynomial activation function, ELM-based algorithms are able to attain good generalization performances in the addressed identification problem.
Legal N-Grams? A Simple Approach to Track the Evolution of Legal Language
Authors: Katz Daniel Martin  , Bommarito II Michael J.  , Seaman Julie  , Agichtein Eugene
Published: February 2025

In this paper, we highlight the potential of n-grams as a vehicle to explore the evolution of legal language. Using the full text corpus of decisions of the U.S. Supreme Court (1946–2005), we very briefly explore the n-gram space and offer some initial results based upon our calculations.
The Democratic Character of New Institutional Governance Arrangements: Comparing Dutch and Belgian Experiences
Authors: Klijn Erik-Hans  , de Rynck Filip  , Skelcher Chris  , Voets Joris
Published: February 2025

This chapter looks at two institutional arrangements that have been designed for the networks around developing the Ghent Kanaalzone in Belgium and the development of the expansion of the port of Rotterdam in The Netherlands. The analysis, focusing on legitimacy, consent and accountability as problems to be solved in networks, shows that that in both countries the arrangement examined created, out of necessity, new forms of legitimacy, accordance and accountability. Through continuous feedback with the institutions of representative democracy the network arrangements and decisions become embedded within the procedures of representative democracy.
Beyond Fragmentation in Public Governance: the Search for Connective Capacity
Authors: Bekkers Victor  , Fenger Menno
Published: February 2025

This chapter sets out to assess the success of the strategies that has been presented in this chapter to deal with the challenges of simultaneous fragmentation and interconnectivity. It reconsiders the main findings of the chapters in this volume, but also tries to go beyond these empirical findings and sketch a number of options that can be followed when dealing with fragmentation. At the same time an assessment will be made of the strong and weak points of these options.
The “Hot” Issues in Business Intelligence: The View of Practitioners
Authors: O'Donnell Peter  , Sipsma Sophie  , Watt Carolyn
Published: February 2025

This paper presents the top 20 challenges currently faced by Business Intelligence practitioners in Australia. The results were obtained from a series of nominal group technique based meetings with BI practitioners designed to elicit the most important of the challenges that they face. The most important issue that practitioners believe they face at the current time is widely seen to be developing BI systems for mobile devices.
Therapeutical Potential of Stem Cells
Authors: Le Gall J.-Y.  , Ardaillou R.
Published: February 2025

The Academy recently discussed the topic of stem cells in the framework of the comments it made about the recommendations attached to the parliamentary commission's mission on the upcoming revision of bioethics laws [1]. The document below results from commission I's work (biology) and brings additional information to a subject in full scientific change, and whose expected medical applications still remain broadly prospective. The results achieved so far underline however, the huge advantage of that research area and encourage to renew our request to provide researchers working in France with the necessary freedom for their research, including on human embryo stem cells.
Mesenchymal Stem Cells
Authors: Busson Elodie  , Thepenier Cédric  , Bolotte Frédéric  , Lataillade Jean-Jacques
Published: February 2025

Mesenchymal stem cells, now commonly called mesenchymal stromal cells (MSCs), represent a rare and heterogeneous population of stem/progenitor cells that reside primarily in the bone marrow (BM) but can also be isolated from different sites such as adipose tissue, peripheral blood, cord blood, liver and fetal tissues. They are described as non-hematopoietic, clonogenic, plastic-adherent cells and capable of differentiating into multiple mesodermal lineages. They lack the inherent ethical consideration of embryonic stem cells and thanks to their capacity to home and engraft into injured tissues and modulate immune response, cell survival and angiogenesis, mesenchymal stromal cells represent a potential novel candidate for regenerative medicine. MSC immune-modulating properties make also them tools for the treatment of graft-versus-host disease (GVHD) as well as severe auto-immune diseases. This clinical interest needs to be substantiated by a clear understanding of the MSC molecular and cellular mechanisms, leading to their use in human therapeutics in the best conditions of security and efficacy. This chapter first presents what is actually known about MSC phenotypic and functional characteristics, focusing on their differentiation, trophic and immune-modulatory capacities. It then briefly describes the prerequisites for MSC culture in vitro for clinical applications.
Computer-aided diagnosis and access on peoples' health status using web technology and mobile devices
Authors: Lambrinidis Christos  , Alepis Efthimios
Published: February 2025

Living in a world that constrains most people to an intensive and hectic way of living along with the plethora of ongoing issues that engross them, the preoccupation and the eagerness for having their health condition checked up has been gradually diminished. This paper presents a novel approach on strongly motivating the thoughtfulness for people's health condition by introducing a system that provides further and broader information on their health issues. Through the resulting system, physicians and businesses, which are involved in medical sciences, are offered a powerful tool, since it conducts diagnoses about their clients by employing their laboratory medical tests. To achieve this, we have applied the Analytical Hierarchical Process algorithm (AHP) on the test results, making the system able to infer whether a patient has an illness or not.
Adopting a Risk-Aware Utility Model for Repeated Games of Chance
Authors: Gemelli Nathaniel  , Hudack Jeffrey  , Oh Jae
Published: February 2025

We present a risk-aware utility model for action selection in 2-player, non-cooperative, repeated games of chance. Our model augments expected utility calculations and adapts to changes in accumulated utility, demonstrating rational game play. Motivated by risk aversion and the utility of wealth, our model is parameterized by an agent's wealth, the payoffs of a game, and the probability associated with gain and loss. Using expected utility combined with our model, we can impose desired behavior onto an agent that mimics more closely the types of behaviors we see in social and economic situations where risk is involved. We define our model theoretically and present empirical results showing the effectiveness of a risk-aware utility model against a Nash equilibrium mixed strategy in a repeated game of chance.
Deliberative Acceptability of Arguments
Authors: Croitoru Cosmina  , K ötzing Timo
Published: February 2025

State of the art extension based argument acceptance is currently biased toward attacks: while the defending extension of an argument a is internally coherent, no such requirement is imposed on its attacking set. On the other hand, if we restrict ourselves only to conflict-free sets of attacking arguments, then we could have different attacking sets for a specified argument a (any two conflicting attackers of a must belong to different a's attacking sets). Having only one defending extension for all these attacking sets would contradict the deliberative nature of argumentation in the real world, where only the coherent sets of attacks matter and the defending sets of arguments depend on the former. In this paper we introduce a new type of acceptability of an argument, in which its attacking and defending sets of arguments are uniformly treated. We call it deliberative acceptance, discuss how this and the classical acceptance notions interrelate and analyze its computational properties. In particular, we prove that the corresponding decision problem is ΠP2
Nested Monte-Carlo Tree Search for Online Planning in Large MDPs
Authors: Baier Hendrik  , Winands Mark H.M.
Published: February 2025

Monte-Carlo Tree Search (MCTS) is state of the art for online planning in large MDPs. It is a best-first, sample-based search algorithm in which every state in the search tree is evaluated by the average outcome of Monte-Carlo rollouts from that state. These rollouts are typically random or directed by a simple, domain-dependent heuristic. We propose Nested Monte-Carlo Tree Search (NMCTS), in which MCTS itself is recursively used to provide a rollout policy for higher-level searches. In three large-scale MDPs, SameGame, Clickomania and Bubble Breaker, we show that NMCTS is significantly more effective than regular MCTS at equal time controls, both using random and heuristic rollouts at the base level. Experiments also suggest superior performance to Nested Monte-Carlo Search (NMCS) in some domains.
Ideal Point Guided Iterative Deepening
Authors: Coego J.  , Mandow L.  , Pérez de la Cruz J.L.
Published: February 2025

Many real world search problems involve different objectives, usually in conflict. In these cases the cost of a transition is given by a cost vector. This paper presents IPID, a new exact algorithm based on iterative deepening, that finds the set of all Pareto-optimal paths for a search problem in a graph with vectorial costs. Formal proofs of the admissibility of IPID are presented, as well as the results of some empirical comparisons between IPID and other approaches based on iterative deepening. Empirical results show that IPID is usually faster than those approaches.
Propositional Planning as Optimization
Authors: Sideris Andreas  , Dimopoulos Yannis
Published: February 2025

Planning as Satisfiability is a most successful approach to optimal propositional planning. Although optimality is highly desirable, for large problems it comes at a high, often prohibitive, computational cost. This paper extends planning as propositional satisfiability to planning as pseudo-boolean optimization. The approach has been implemented in a planner called PseudoSATPLAN, that follows the classic solve and expand method of the SATPLAN algorithm, but at each step it seeks to maximize the number of goals that can be achieved. The utilization of the achieved goals at subsequent steps opens up the possibility of implementing various strategies. The method essentially splits a planning problem into smaller subproblems, and employs various techniques for solving them fast. Although PseudoSATPLAN cannot guarantee the optimality of the generated plans, it aims at computing solutions of good quality. Experimental results show that PseudoSATPLAN can generate parallel plans of high quality for problems that are beyond the reach of the existing implementations of the planning as satisfiability framework.
Multi-unit Auctions with a Stochastic Number of Asymmetric Bidders
Authors: Vetsikas Ioannis A.  , Stein Sebastian  , Jennings Nicholas R.
Published: February 2025

Existing work on auctions assumes that bidders are symmetric in their types — they have the same risk attitude and their valuations are drawn from the same distribution. This is unrealistic in many real-world applications, where highly heterogeneous bidders with different risk attitudes and widely varying valuation distributions commonly compete with each other. Using computational service auctions that are emerging in cloud and grid settings as a motivating example, we examine how an intelligent agent should bid in such multi-unit auctions with asymmetric bidders. Specifically, we describe the equilibrium bidding strategies in three different settings that are distinguished by the levels of uncertainty about the types of other agents. First, we consider a setting with full knowledge about all agents' types, then we consider the case where the types are uncertain, but the number of bidders is known. Finally, we consider the case where both the number of bidders and their types are uncertain. Our experiments show that using the equilibrium strategies derived from our full analysis leads to increased utility (typically 20–25%) for the participants compared to previous state-of-the-art strategies.
Advances in Distributed Branch and Bound
Authors: Otten Lars  , Dechter Rina
Published: February 2025

We describe a distributed version of an advanced branch and bound algorithm over graphical models. The crucial issue of load balancing is addressed by estimating subproblem complexity through learning, yielding impressive speedups on various hard problems using hundreds of parallel CPUs.
Multi-Agent Logic based on Temporary Logic TS4
Authors: Rybakov Vladimir
Published: February 2025

In this paper we study multi-agents’ non-linear temporal logic TS4K_nbased on arbitrary (in particular, non-linear, finite or infinite) frames with reflexive and transitive accessibility relations, and individual symmetric accessibility relations Rifor agents. Our framework uses conception of interacting agents implemented via arbitrary finite paths of transitions by agents accessibility relations. Main problems we are dealing here are decidability and satisfiability problems for this logic. We prove that TS4Kn
A fuzzy negotiation model to assign variable’s domain in Constraint Satisfaction Problems: An agent based collaborative engineering modeling case
Authors: Mejía-Gutiérrez Ricardo  , Cálad-álvarez Alejandro  , Zuluaga-Holguín Daniel
Published: February 2025

Knowledge sharing among partners from a distributed engineering team is becoming more critical for decision making. The work presented in this article proposes to support users of an agent based application for collaborative product design, during the definition of an engineering problem under a Constraint Satisfaction Problem (CSP) approach. The scope of this work covers the domains definition for variables from the CSP distributed model. A semiautomatic negotiation model is proposed in order to give users suggestions about a preferred domain for a variable that is used for more than one expert. A set of quantitative indexes measure the competence that users have over variables in the model, helping the system in decision making. A fuzzy inference system is used to calculate user’s competence index and suggestions are made based on a fuzzy approach in order to achieve trade-offs in collaborative domains definition.
A Heuristic TRIZ Problem Solving Approach based on Semantic Relatedness and Ontology Reasoning
Authors: Yan Wei  , Zanni-Merk Cecilia  , Rousselot François  , Cavallucci Denis  , Collet Pierre
Published: February 2025

The theory of inventive problem solving (TRIZ) was developed to solve inventive problems in different industrial fields. In recent decades, modern innovation theories and methods proposed several different knowledge sources, whose use requires extensive knowledge about different engineering domains. In order to facilitate the use of the TRIZ knowledge sources, this paper explores a heuristic TRIZ problem solving approach. Firstly, TRIZ users start solving inventive problem with the TRIZ knowledge source of their choice. Then other similar knowledge sources are used according to a calculation of semantic relatedness. Finally, heuristic solutions are returned by ontology reasoning on the knowledge sources. The case of a “Diving Fin” is used to show the heuristic TRIZ problem solving process in detail.
User Personalization via W-kmeans
Authors: Bouras Christos  , Tsogkas Vassilis
Published: February 2025

With the rapid explosion of online news articles, predicting userbrowsing behavior using collaborative filtering techniques has gained much attention in the web personalization area. However, common collaborative filtering techniques suffer from low accuracy and performance. This research proposes a new personalized recommendation approach that integrates user and text clustering based on our developed algorithm, W-kmeans, with other information retrieval techniques, like text categorization and summarization in order to provide users with the articles that match their profiles. Our system can easily adapt over time to divertive user preferences. Furthermore, experimental results show that by aggregating multiple other information retrieval techniques like categorization, summarization and clustering, our recommender generates results that outperform the cases when clustering is not applied.
A Human-Computer Interaction System Facilitating Communication with Hearing-Impaired People
Authors: Koziol Wojciech  , Wojtowicz Hubert  , Sikora Kazimierz  , Wajs Wieslaw
Published: February 2025

The following publication is devoted to the mechanisms governing a system which facilitates communication with hearing-impaired people. The key element of the system is an application which translates written Polish texts into the sign language. It uses two complementary databases: the main one consists of a list of lexemes with their characterization, whereas, the latter is a set of grammatical and semantic facts. The message is conveyed in several phases. The core (ideographic) information is complemented by the mimic signs and synthesized speech. The main application joins all the modules and serves as the interface. The authors claim that the system will be helpful in various offices, healthcare centers, schools, etc.
A Complex System Approach for Smart Grid Analysis and Modeling
Authors: Guérard Guillaume  , Ben Amor Soufian  , Bui Alain
Published: February 2025

Smart Grid is a vague concept with little theoretical studies. We propose in this paper a state of the art on Smart Grids to clarify the concept and identify the important issues.
A New Method for Non-Dominant Motion Skill Learning by Using Motion Navigator
Authors: Soga Masato  , Ishii Kazuki  , Nishino Tomoyasu  , Taki Hirokazu
Published: February 2025

In this paper, we propose two new methods to learn and practice non-dominant motion using Motion Converter and Motion Navigator. One is a method of non-dominant motion practice by following reversed dominant motion animation. The other is awareness of non-dominant motion error by dominant body site. We think that both methods are complementary each other. Therefore, a learner can practice his/her non-dominant motion and get awareness of non-dominant motion error by trying both methods.
On the Use of Presumptions in Structured Defeasible Reasoning
Authors: Martinez Maria Vanina  , García Alejandro J.  , Simari Guillermo R.
Published: February 2025

In this work we introduce an extension of an structured argumentation system in which presumptions are fully integrated in the reasoning mechanism. A presumption is defined as a piece of information that is tentatively taken to be true, usually in the absence of acceptable reasons to the contrary. In Presumptive Defeasible Logic Programming (PreDeLP), arguments can be built from both facts and presumptions. We analyze several criteria to compare arguments in PreDeLP, and highlight one possibility that captures the semantic difference between presumptions and facts or defeasible rules. On top of PreDeLP we develop a defeasible approach to argumentation-based diagnostic reasoning. The use of presumptions permits to extend the reasoning beyond factual information, creating in this way a universe of possible scenarios that support or interfere with a claim. We characterize the set of possible scenarios for and against a claim and identify those that best explain the warrant status of the query.
Tactics and Concessions for Argumentation-based Negotiation
Authors: Hadidi Nabila  , Dimopoulos Yannis  , Moraitis Pavlos
Published: February 2025

Argumentation-based negotiation has gained increasing prominence in the multi-agent field over the last years. There is currently a long literature on the use of argumentation in negotiation and especially the modeling of negotiation protocols or decision making mechanisms. However the study of strategic issues that define the behavior of an agent during the negotiation has been largely neglected. This work fills this gap by providing, profile, behavior and time constraints based tactics that can be combined together to implement complex strategies similar to those studied in game-theoretic negotiation. These different tactics lead to different types of concessions. An experimental evaluation shows how tactics and concessions may influence the negotiation length and outcome, under the assumptions of deadlines and the availability of information on the opponent.
Implementing ArguBlogging
Authors: Snaith Mark  , Bex Floris  , Lawrence John  , Reed Chris
Published: February 2025

In this paper, we present ArguBlogging, a simple tool that allows blog users to directly respond to text on a web page, publishing the response to their blog while simultaneously capturing the argumentative structure in the Argument Web via the Argument Interchange Format.
Automatic Inference of Base Forms for Multiword Terms in Lithuanian
Authors: Boizou Loïc  , Grigonytė Gintarė  , Rimkutė Erika  , Utka Andrius
Published: February 2025

This paper reports on a specific problem of automatic terminology extraction in Lithuanian – base form inference. While the process of lemmatisation is properly carried out by existing tools, problems arise with normalizing multiword terms. It can be described as the discrepancy between the base form (i. e. lemma) of a term and the sequence of the base forms of constituent lexical items within a term. Lithuanian is a strongly inflected language and the lemmatisation of each word separately within a multiword term breaks the syntactic relations expressed by inflection (case, gender, number) which need to be kept in order to ensure the cohesion of the term.
Survey on 2D and 3D Human Pose Recovery
Authors: Perez-Sala Xavier  , Escalera Sergio  , Angulo Cecilio
Published: February 2025

Human Pose Recovery approaches have been studied in the field of Computer Vision for the last 40 years. Several approaches have been reported, and significant improvements have been obtained in both data representation and model design. However, the problem of Human Pose Recovery in uncontrolled environments is far from being solved. In this paper, we define a global taxonomy to group the model based methods and discuss their main advantages and drawbacks.
An Entity Relationship Extraction Model Based on Chameleon Clustering Algorithm
Authors: Huijuan Zhang  , Shixuan Sun
Published: February 2025

Current relationship extraction models are human centered. It doesn't consider the impact of time attribute and only focuses on extracting whole relationship network of a group. In accordance with these problems, this paper proposes an entity relationship extraction model based on Chameleon Clustering Algorithm. By collecting and analyzing interactions between entities, the new model can find out sub-clusters of a group and extract relationship between these sub-clusters. It fully considers the impact of time attribute. With a real data set, the experiments demonstrate that sub-clusters and relationship between them can be found by the model we proposed efficiently. It lays a solid foundation for further study of entity relationship networks.