bluuebunny/crossref_metadata_2025 huggingface dataset:
Extraction of Places Related to Flickr Tags
Authors: Baba Yukino  , Ishikawa Fuyuki  , Honiden Shinichi
Published: February 2025

Geographic information systems use databases to map keywords to places. These databases are currently most often created by using a top-down approach based on the geographic definitions. However, there is a problem with this approach in that these databases only contain location definitions such as addresses and place names, which does not allow for searches using keywords other than these words. Additionally, they do not give any information on the popularity, e.g., which is more popular among the places indexed by the same keyword. A bottom-up approach, based on the actual usage of words, can address these problems. We propose a method to aggregate tagging data and extract places related to a tag using the pair of a tag and a geo-tagged photo. We target the co-occurrence of a tag and the geolocation and represent the places related to a tag as a probability distribution over the longitudes and latitudes. We applied our method to data on the photo sharing service Flickr and experimentally confirmed that our method made it possible to highly-accurately extract places related to tags. Our direct bottom-up approach enables the extraction of place information that is not obtained by using traditional top-down approaches.
The Epistemic View of Belief Merging: Can We Track the Truth?
Authors: Everaere Patricia  , Konieczny Sébastien  , Marquis Pierre
Published: February 2025

Belief merging is often described as the process of defining a base which best represents the beliefs of a group of agents (a profile of belief bases). The resulting base can be viewed as a synthesis of the input profile. In this paper another view of what belief merging aims at is considered: the epistemic view. Under this view the purpose of belief merging is to best approximate the true state of the world. We point out a generalization of Condorcet's Jury Theorem from the belief merging perspective. Roughly, we show that if the beliefs of sufficiently many reliable agents are merged then in the limit the true state of the world is identified. We introduce a new postulate suited to the truth tracking issue. We identify some merging operators from the literature which satisfy it and other operators which do not.
EP for Efficient Stochastic Control with Obstacles
Authors: Mensink Thomas  , Verbeek Jakob  , Kappen Bert
Published: February 2025

We address the problem of continuous stochastic optimal control in the presence of hard obstacles. Due to the non-smooth character of the obstacles, the traditional approach using dynamic programming in combination with function approximation tends to fail. We consider a recently introduced special class of control problems for which the optimal control computation is reformulated in terms of a path integral. The path integral is typically intractable, but amenable to techniques developed for approximate inference. We argue that the variational approach fails in this case due to the non-smooth cost function. Sampling techniques are simple to implement and converge to the exact results given enough samples. However, the infinite cost associated with hard obstacles renders the sampling procedures inefficient in practice. We suggest Expectation Propagation (EP) as a suitable approximation method, and compare the quality and efficiency of the resulting control with an MC sampler on a car steering task and a ball throwing task. We conclude that EP can solve these challenging problems much better than a sampling approach.
An Axiom System for a Spatial Logic with Convexity
Authors: Trybus Adam
Published: February 2025

This paper presents a part of work in progress on axiomatizing a spatial logic with convexity and inclusion predicates (hereinafter called convexity logic), with some intended interpretation over the real plane. More formally, let Lconv,≤be a language of first order logic and two non-logical primitives: conv (interpreted as a property of a set of being convex) and ≤ (interpreted as the set inclusion relation). We let variables range over regular open rational polygons in the real plane (denoted ROQ(R2)). We call the tuple M = ⟨ROQ, conv, ≤⟩ — where primitives are defined as indicated above — a standard model. We propose an axiomatization of the theory of M and prove soundness and completeness for this axiomatization.
Fast Local Search for Fuzzy Job Shop Scheduling
Authors: Puente Jorge  , Vela Camino R.  , González-Rodríguez Inés
Published: February 2025

In the sequel, we propose a new neighbourhood structure for local search for the fuzzy job shop scheduling problem. This is a variant of the well-known job shop problem, with uncertainty in task durations modelled using fuzzy numbers and where the goal is to minimise the expected makespan of the resulting schedule. The new neighbourhood structure is based in changing the relative order of subsequences of tasks within critical blocks. We study its theoretical properties and provide a makespan estimate which allows to select only feasible neighbours while covering a greater portion of the search space than a previous neighbourhood from the literature. Despite its larger search domain, experimental results show that this new structure notably reduces the computational load of local search with respect to the previous neighbourhood while maintaining or even improving solution quality.
Relative-Order Abstractions for the Pancake Problem
Authors: Helmert Malte  , Röger Gabriele
Published: February 2025

The pancake problem is a famous search problem where the objective is to sort a sequence of objects (pancakes) through a minimal number of prefix reversals (flips). The best approaches for the problem are based on heuristic search with abstraction (pattern database) heuristics. We present a new class of abstractions for the pancake problem called relative-order abstractions. Relative-order abstractions have three advantages over the object-location abstractions considered in previous work. First, they are size-independent, i.e., do not need to be tailored to a particular instance size of the pancake problem. Second, they are more compact in that they can represent a larger number of pancakes within abstractions of bounded size. Finally, they can exploit symmetries in the problem specification to allow multiple heuristic lookups, significantly improving search performance over a single lookup. Our experiments show that compared to object-location abstractions, our new techniques lead to an improvement of one order of magnitude in runtime and up to three orders of magnitude in the number of generated states.
Temporal Relations Learning with a Bootstrapped Cross-document Classifier
Authors: Mirroshandel Seyed Abolghasem  , Ghassem-Sani Gholamreza
Published: February 2025

The ability to accurately classify temporal relation between events is an important task for a large number of natural language processing applications such as Question Answering (QA), Summarization, and Information Extraction. This paper presents a weakly-supervised machine learning approach for classification of temporal relation between events. In the first stage, the algorithm learns a general classifier from an annotated corpus. Then, it applies the hypothesis of “one type of temporal relation per discourse” and expands the scope of “discourse” from a single document to a cluster of topically-related documents. By combining the global information of such a cluster with local decisions of a general classifier, we propose a novel bootstrapping cross-document classifier to extract temporal relations between events. Our experiments show that without any additional annotated data, the accuracy of the proposed algorithm is at least 7% higher than that of the pattern based state of the art system.
On the Verification of Very Expressive Temporal Properties of Non-terminating Golog Programs
Authors: Claßen Jens  , Lakemeyer Gerhard
Published: February 2025

The agent programming language GOLOG and the underlying Situation Calculus have become popular means for the modelling and control of autonomous agents such as mobile robots. Although such agents' tasks are typically open-ended, little attention has been paid so far to the analysis of non-terminating GOLOG control programs. Recently we therefore introduced a logic that allows to express properties of Golog programs using operators from temporal logics while retaining the full first-order expressiveness of the Situation Calculus. Combining ideas from classical symbolic model checking with first-order theorem proving we presented a verification method for a restricted subclass of temporal properties. In this paper, we extend this work by considering arbitrary temporal formulas. Our algorithm is inspired by classical 𝒞𝒯ℒ* model checking, but introduces techniques to cope with arbitrary first-order quantification.
Adaptive Markov Logic Networks: Learning Statistical Relational Models with Dynamic Parameters
Authors: Jain Dominik  , Barthels Andreas  , Beetz Michael
Published: February 2025

Statistical relational models, such as Markov logic networks, seek to compactly describe properties of relational domains by representing general principles about objects belonging to particular classes. Models are intended to be independent of the set of objects to which these principles can be applied, and it is assumed that the principles will soundly generalize across arbitrary sets of objects. In this paper, we point out limitations of models that seek to represent the corresponding principles with a fixed set of parameters and discuss the conditions under which the soundness of fixed parameters is indeed questionable. We propose a novel representation formalism called adaptive Markov logic networks to allow more flexible representations of relational domains, which involve parameters that are dynamically adjusted to fit the properties of an instantiation by phrasing the model's parameters as functions over attributes of the instantiation at hand. We empirically demonstrate the value of our learning and representation system on a simple but well-motivated example domain.
Project Scheduling as a Disjunctive Temporal Problem
Authors: Oddi Angelo  , Rasconi Riccardo  , Cesta Amedeo
Published: February 2025

The main result of the paper is the reduction of the RCPSP/max problem to a Disjunctive Temporal Problem that allows customization of specific properties within a backtracking search procedure for makespan optimization. In addition, a branching strategy is proposed able to deduce new constraints which explicitly represent infeasible or useless search paths. A new variable ordering heuristic (called clustering) is also used which provides a further boosting to the algorithm's effectiveness.
Learning action effects in partially observable domains
Authors: Mourão Kira  , Petrick Ronald P.A.  , Steedman Mark
Published: February 2025

We investigate the problem of learning action effects in partially observable STRIPS planning domains. Our approach is based on a voted kernel perceptron learning model, where action and state information is encoded in a compact vector representation as input to the learning mechanism, and resulting state changes are produced as output. Our approach relies on deictic features that assume an attentional mechanism that reduces the size of the representation. We evaluate our approach on a number of partially observable planning domains, and show that it can quickly learn the dynamics of such domains, with low average error rates. We show that our approach handles noisy domains, conditional effects, and that it scales independently of the number of objects in a domain.
Selection of Parameters and Algorithms in Multiple-Goal Task Realization
Authors: Gueta Lounell B.  , Chiba Ryosuke  , Arai Tamio  , Ueyama Tsuyoshi  , Ota Jun
Published: February 2025

Realizing a multiple-goal task is a complicated optimization problem due to several parameters. Since the quality of the optimized parameter is dependent on the algorithm, evaluation on various algorithms can be necessary but will require substantial computational resources. Therefore, appropriate parameters and algorithms have to be selected in order to derive a good quality solution within a reasonable amount of time. Such selection is difficult because it would require knowledge of the task to be realized. In this paper, the concept of hyperheuristic is utilized. The ant colony system exhibits a promising result as the hyperheuristic in a time-constrained optimization.
A Thermodynamic Framework for Robot Colony Control
Authors: D'Angelo Antonio  , Pagello Enrico
Published: February 2025

In the last decade the development of multirobot systems has shown with growing evidence how a well-balanced deliberative-reactive coordination is the key issue to provide the group with an efficient and robust collective behavior. Usually, but not necessarily, deliberation is linked to the planning dynamical role exchange whereas reactivity is associated with the ability of the system to stress any condition which could fertilize cooperation. Using a chemical metaphor we could say that reactive cooperation should emerge from the interaction between individiduals through an appropriate catalyst whose availability increases as cooperation increases. In the paper we present an attempt to satisfy the constraint by maintaining at the subsymbolic level, as long as it is possible, all the relevant information to coordinate a multirobot system. To this aim we model the group of robots using the roboticle framework and we assume a thermal metaphor where temperature and conductivity are the quantities which trigger the individual dynamics to make emerging the collective behavior of the group.
Innovation in Monitoring Technologies for Underground Structures
Authors: Soga Kenichi  , Chaiyasarn Krisada  , Viola Fabio  , Yan Jize  , Seshia Ashwin  , Cipolla Roberto
Published: February 2025

One of the greatest challenges facing civil engineers in the 21st century is the stewardship of ageing civil engineering infrastructure. Nowhere is this more apparent than in underground structures in the major cities around the world. Much of them were constructed more than half a century ago and there is widespread evidence of deterioration. Advances in the development of computer vision and miniature micro-electro-mechanical sensors (MEMS) offer intriguing possibilities that can radically alter the paradigms underlying existing methods of condition assessment and monitoring of such infrastructure. This paper discusses potentials of these technologies for monitoring underground infrastructure.
The European project “Technology Innovation in Underground Construction” – Overview of IT results
Authors: Beer Gernot
Published: February 2025

The European project “Technology Innovation in Underground Construction” is the biggest single research initiative ever undertaken on the topic. Some innovations that resulted from the project and that are associated with some topics of the conference are presented.
Research on failure modes in fractured rock masses under triaxial compression using Distinct Element Method
Authors: Fan Lei  , Tang Huiming  , Zhou Huoming
Published: February 2025

Because of large number of discontinuities existing in rock mass, the mechanics and failure modes are controlled by the rock mass structure characteristics. The numerical test method, integrating the results of in-situ investigations, laboratory and in-site tests, can provide a new approach to study the mechanical behavior and failure theory of fractured rock mass. The fractured sandstone rock masses in the west area of Hubei Province were chosen as a case study. Based on the statistic analyses of discontinuities, the structure models of rock masses are founded with Monte-Carlo method. Then a series of numerical compress tests using Distinct Element Method were carried out to discuss the failure strengths and failure modes in rock masses. The study shows that, the failure strengths and failure modes have a strong dependency on model size, confining pressure and loading orientation. In addition, the fractured rock mass shows anisotropic behavior, but this behavior is insignificant with the increase of confining pressure and the side length of rectangle model. The failure modes in fractured rock masses can be generalized into two types. One occurs in a complex way in small models under high confining pressures, i.e., combining sliding and bursting of discontinuities and shear bands in the rock matrix. Another takes place with slide of discontinuities in small models under low confining pressures or in large models. However, the pathways of these two failure modes both have an angle of 30° to 40° to the loading orientation.
Two-Agent Conflict Resolution with Assumption-Based Argumentation
Authors: Fan Xiuyi  , Toni Francesca  , Hussain Adil
Published: February 2025

Conflicts exist in multi-agent systems. Agents have different interests and desires. Agents also hold different beliefs and may make different assumptions. To resolve conflicts, agents need to better convey information between each other and facilitate fair negotiations that yield jointly agreeable outcomes. In this paper, we present a two-agent conflict resolution scheme developed under Assumption-Based Argumentation (ABA). Agents represent their beliefs and desires in ABA. Conflicts are resolved by merging conflicting arguments. We also discuss the notion of fairness and the use of argumentation dialogue in conflict resolution.
On Extension Counting Problems in Argumentation Frameworks
Authors: Baroni Pietro  , Dunne Paul E.  , Giacomin Massimiliano
Published: February 2025

We consider the problem of counting (without explicitly enumerating) extensions prescribed by multiple-status semantics in abstract argumentation. Referring to Dung's traditional stable and preferred semantics and to the recently introduced resolution-based grounded semantics (GR*), we show that in general extension counting is computationally hard (actually #P-complete). We then identify non-trivial topological classes of argumentation frameworks where extension counting is tractable. In particular we show, by providing and analyzing the relevant algorithms, that in symmetric argumentation frameworks counting GR* extensions is tractable (but is still hard for stable and preferred estensions), while counting is tractable for all the considered semantics in tree-like argumentation frameworks.
Using Defeasible Logic Programming for Argumentation-Based Decision Support in Private Law
Authors: Beierle C.  , Freund B.  , Kern-Isberner G.  , Thimm M.
Published: February 2025

Legal reasoning is one of the most obvious application areas for computational models of argumentation as the exchange of arguments and counterarguments is the established means for making decisions in law. In this paper we employ Defeasible Logic Programming (DeLP) for representing legal cases and for giving decision-support, exemplary for private law. We give a formalization of legal provisions that can be used easily by judges for supporting their decision process and present a working system that resembles the decision-making in legal reasoning, in particular, with respect to the burden of proof.
A formal analysis of the AIF in terms of the ASPIC framework
Authors: Bex Floris  , Prakken Henry  , Reed Chris
Published: February 2025

In order to support the interchange of ideas and data between different projects and applications in the area of computational argumentation, a common ontology for computational argument, the Argument Interchange Format (AIF), has been devised. One of the criticisms levelled at the AIF has been that it does not take into account formal argumentation systems and their associated argumentation-theoretic semantics, which are part of the main focus of the field of computational argumentation. This paper aims to meet those criticisms by analysing the core AIF ontology in terms of the recently developed ASPIC argumentation framework.
Fitting System Functionality to Business Needs: Alignment issues and challenges
Authors: Rolland Colette
Published: February 2025

Fitting information systems to business needs is considered equally important by both, the Requirements Engineering and MIS communities. Even though alignment/fit clearly appears as desirable, a number of issues still remain unsolved. This paper gives to fitness a central position and introduces the notion of a fitness relationship and its measurement. It highlights two sets of issues, one involved in understanding this relationship and the second in engineering it. It also points out broad directions and trends in resolving these issues.
A quantitative model to evaluate post-implementation efficiency of Scrum
Authors: de Jager G.P.  , Huisman H.M.  , Kruger H.A.
Published: February 2025

In order to improve the information system development process many companies have adopted system development methodologies. Various evaluation methods and frameworks exist in the literature to assist companies during their adoption phase. However, a need was identified to evaluate the efficiency of a system development methodology after adoption. In an era where there is a reappraisal of the usefulness of system development methodologies it is essential to have a valid and reliable method of evaluation. The aim of this paper is to propose an evaluation model to measure post-implementation efficiency of a software development methodology. Data Envelopment Analysis, a linear programming method, is investigated as a means to evaluate efficiency of a SDM after adoption. This paper focus on the Scrum software development methodology as it is a popular methodology in use today. With Data Envelopment Analysis it is possible to classify different companies' use of Scrum as efficient or inefficient. The results also make it possible to identify specific areas in a company that needs improvement. These individual recommendations can be applied to increase the post-implementation efficiency of a company's systems development methodology.
A Study of Building a Database System based on ISSEI Data Management Method
Authors: Hayashida Shogo
Published: February 2025

A new data management method called ISSEI was proposed in the previous report [1], to avoid slowing down of data retrieving time for the database that has an inherent nature of ever growing data volume. ISSEI's data handling performance, namely adding, retrieving, updating and deleting data were evaluated. Through the evaluation, it was confirmed that ISSEI's data handling performances are not dependent on the database size, while the conventional DBMS such as MS SQL Server requires more time for data handling as the database size grows [6].This paper deals with evaluations of ISSEI's performance limitation on system operation and maintenance toward applying ISSEI to a corporate knowledge database that has growing data volume. Through the evaluations, interesting results were obtained. One interesting result is that ISSEI's performance dependency on the data volume size is maintained up to the upper capacity of hard disk. Another interesting result is that data recovery performance of ISSEI is drastically degraded by the length of data records. From the two results, it is concluded whether ISSEI can be applied for the database that has growing data volume or not.
Issues with a Ubiquitous Printing System, PrinterSurf
Authors: Murayama Yuko  , Saito Yoshia
Published: February 2025

Although we have enjoyed exchanging information electronicly these days, paper is still a useful media for communications. From this viewpoint, a printer is a fascinating device to connect the cyber space to the real world. In this research we propose a peer-to-peer remote printing system. Printer devices, however, remain yet large and heavy because they require papers and inks. It is still difficult to carry around the printers devices. In this paper, we propose an advanced printing system for ubiquitous computing, PrinterSurf which provides a flexible printing service anytime anywhere via computer networks using PCs and closely-located printer devices. This paper introduces our research on PrinterSurf as well as some issues to be dealt with in future.
Resource-bounded Outlier Detection using Clustering Methods
Authors: Torgo Luis  , Soares Carlos
Published: February 2025

This paper describes a methodology for the application of hierarchical clustering methods to the task of outlier detection. The methodology is tested on the problem of cleaning Official Statistics data. The goal is to detect erroneous foreign trade transactions in data collected by the Portuguese Institute of Statistics (INE). These transactions are a minority, but still they have an important impact on the statistics produced by the institute. The detectiong of these rare errors is a manual, time-consuming task. This type of tasks is usually constrained by a limited amount of available resources. Our proposal addresses this issue by producing a ranking of outlyingness that allows a better management of the available resources by allocating them to the cases which are most different from the other and, thus, have a higher probability of being errors. Our method is based on the output of standard agglomerative hierarchical clustering algorithms, resulting in no significant additional computational costs. Our results show that it enables large savings by selecting a small subset of suspicious transactions for manual inspection, which, nevertheless, includes most of the erroneous transactions. In this study we compare our proposal to a state of the art outlier ranking method (LOF) and show that our method achieves better results on this particular application. The results of our experiments are also competitive with previous results on the same data. Finally, the outcome of our experiments raises important questions concerning the method currently followed at INE concerning items with small number of transactions.
Comparison of the SemTi-Kamols and Tesnière's Dependency Grammars
Authors: Nešpore Gunta  , Saulīte Baiba  , Bārzdiņš Guntis  , Grūzītis Normunds
Published: February 2025

The dependency approach, originally developed by Lucien Tesnière, has become a popular model of syntactic representation. However, the state-of-the-art dependency parsers and annotation schemes typically discard some relevant features of the original Tesnière's model, retaining only the concept of dependency relations between individual words. The SemTi-Kamols grammar model attempts to return to the Tesnière's key concepts supplementing the approach with some additional features and concepts. The aim of this paper is to explain how the Semti-Kamols approach relates to and differs from the original Tesnière's approach, discussing the similarities and differences.
Cloud Computing for the Humanities: Two Approaches for Language Technology
Authors: Wilcock Graham
Published: February 2025

The paper describes Aelred, a web application that demonstrates the use of language technology in the Google App Engine cloud computing environment. Aelred serves up English literary texts with optional concordances for any word and a range of linguistic annotations including part-of-speech tagging, shallow parsing, and word sense definitions from WordNet.
Latvian Text-to-Speech Synthesizer
Authors: Pinnis Mārcis  , Auziņa Ilze
Published: February 2025

The paper describes the development of the Latvian Text-to Speech Synthesizer at the Institute of Mathematics and Computer Science (University of Latvia).
The Role of Ontologies in the Anonymization of Textual Variables
Authors: Martínez Sergio  , Sánchez David  , Valls Aïda  , Batet Montserrat
Published: February 2025

The exploitation of sensible data associated to individuals requires a proper anonymization in order to preserve the privacy. Even though several masking methods have been designed for numerical data, very few of them deal with textual information. During the masking process, information loss should be minimized in order to enable a proper analysis of data with data mining methods. In the case of textual data, the quality of the anonymized dataset is closely related to the preservation of semantics, a dimension which has been only shallowly considered in some previous works, by using small and ad-hoc hierarchies of words. In this work we want to study the use of large and standard ontologies as the base to perform the anonymization of textual variables. We will evaluate the role of ontologies in preserving the utility of the anonymized information when a partition of the objects is done with unsupervised clustering methods. Results show that by exploiting detailed ontologies, one is able to improve the preservation of the data semantics in comparison to approaches based on ad-hoc structures and data distribution metrics.
Semantic Clustering Using Multiple Ontologies
Authors: Batet Montserrat  , Valls Aïda  , Gibert Karina  , Sánchez David
Published: February 2025

Data mining tools able to semantically interpret textual or linguistic data are acquiring a growing importance. Moreover, the development of large ontologies for general and specific domains provides new tools to include background knowledge into data mining techniques such as clustering. In this paper we present an unsupervised clustering method that exploits the semantics of categorical data by means of ontologies, and it is also able to manage numerical data. Our method is able to use different ontologies in order to assess the meaning of the values during the clustering process, leading to a set of clusters with a clearer semantic interpretation in a particular domain. The influence of using one or several ontologies is analyzed by using real data collected from visitors to the Ebre Delta Natural Park, which is a protected natural reserve in Catalonia (Spain).
WizArg: Visual Argumentation Framework Solving Wizard
Authors: Gómez-Sebastià Ignasi  , Nieves Juan Carlos
Published: February 2025

Extension-based argumentation semantics have shown to be a suitable approach for performing practical reasoning. An important concern in extension-based-argumentation semantics is the computational complexity of the decision problems that has been shown to range from NP-complete to Π2(p)
Simple Ecological Rules Yield Complex Agent Networks
Authors: Lurgi Miguel  , Robertson David
Published: February 2025

In complex natural systems (such as ecological systems) it is common for those studying the macro-dynamics of systems to aim to describe, as simply as possible, the interactions between individuals occupying different niches in a system and to validate these by studying whether they account for the complex network of relationships observed in the actual system. We explore a similar principle applied to multi-agent systems: we develop interactions among intelligent agents; these interactions produce complex networks of relationships among the entities in the system in a similar fashion in which ecological networks are formed in nature. The study of the topological features displayed by these networks is helpful for determining the stability of the system of software agents and its relation to the complexity of the network itself. An interaction centred approach for coordination and knowledge sharing among artificial agents is adopted for the implementation of the system.
Biological and and Psycholinguistic Influences on Architectures For Natural Language Processing
Authors: Sowa John F.
Published: February 2025

Systems for natural language processing (NLP) are based on some linguistic theory adapted to available computational technology. Since the earliest NLP systems, a variety of linguistic, philosophical, logical, and computational issues have created controversies about the design choices. Today, advances in technology have created new options, and insights from neuroscience can help guide the choices. Section 1 summarizes the controversies and the shifting design choices caused by different theories and technologies. Section 2 presents neural evidence about connections among language areas of the brain and their implications on the design. Section 3 summarizes psycholinguistic considerations on the design and implementation of conceptual graphs. Section 4 describes how the VivoMind Language Processor (VLP) implements these design options. In recent tests, they enabled VLP to get significantly better results than more traditional designs.
The Role of the Basal Ganglia – Anterior Prefrontal Circuit as a Biological Instruction Interpreter
Authors: Stocco Andrea  , Lebiere Christian  , O'Reilly Randall C.  , Anderson John R.
Published: February 2025

Intelligent and versatile behavior requires the capability of adapting to novel and unanticipated situations. When facing novel and unexpected tasks, a fast and general solution consists in creating new declarative task representations, and subsequently acting upon them. Although this mechanism seems straightforward in general terms, it poses significant difficulties to be implemented in a biological model, and the exact neural substrates of this process are still unknown. Based on the analysis of two different computational models, we hypothesized that the brain circuit for interpreting instructions would comprise the aPFC (holding dependencies among specialized cortical areas) and the basal ganglia (orchestrating the exchange of information among regions). To verify this hypothesis, we designed and ran an fMRI experiment where participants had to perform changing tasks that consisted of different combinations of atomic cognitive operations. Both models and experimental data suggest that the aPFC is critical in representing abstract knowledge that reflects planned cognitive operations. This is consistent with the late appearance of aPFC in the evolution of the human brain, and its role in enabling human intelligence and culture. On the other hand, results and simulations show that the effect of this cortical region is made possible by the contribution of the basal ganglia circuit, which works as a general-purpose interpreter of declarative knowledge.
Validating a High Level Behavioral Representation Language (HERBAL): A Docking Study for ACT-R
Authors: Zhao Changkun  , Paik Jaehyon  , Morgan Jonathan H.  , Ritter Frank E.
Published: February 2025

We present a docking study for Herbal, a high-level behavioral representation language based on the problem space computational model. This study docks an ACT-R model created with Herbal to one created by hand. This comparison accomplishes several things. First, we believe such studies are necessary for achieving and demonstrating the theoretical rigor and repeatability promised by high-level representation languages. Second, it is necessary to evaluate the effectiveness and efficiency of high-level cognitive modeling languages if they are to make a significant impact in either the cognitive or social sciences. Third, this kind of study provides an opportunity to test Herbal's ability to produce ACT-R models from a GOMS-like representation that contains hierarchical methods, memory capacity, and control constructs. Finally, this study provides an example model for future validation work in this area. Our study addresses each of these points by docking Pirolli's [1] price finding model in ACT-R with the same model written in Herbal. We extended Herbal to support more memory types, and in the process may have extended the PSCM.
Online Event Segmentation in Active Perception using Adaptive Strong Anticipation
Authors: Nery Bruno  , Ventura Rodrigo
Published: February 2025

The segmentation of a stream of perceptual inputs a robot receives into discrete and meaningful events poses challenge in bridging the gap between internal cognitive representations, and the external world. Event Segmentation Theory, recently proposed in the context of cognitive systems research, sustains that humans segment time into events based on matching perceptual input with predictions. In this paper we propose a framework for online event segmentation, targeting robots endowed with active perception. Moreover, sensory processing systems have an intrinsic latency, resulting from many factors such as sampling rate, and computational processing, and which is seldom accounted for. This framework is founded on the theory of dynamical systems synchronization, where the system considered includes both the robot and the world coupled (strong anticipation). An adaption rule is used to perform simultaneous system identification and synchronization, and anticipating synchronization is employed to predict the short-term system evolution. This prediction allows for an appropriate control of the robot actuation. Event boundaries are detected once synchronization is lost (sudden increase of the prediction error). An experimental proof of concept of the proposed framework is presented, together with some preliminary results corroborating the approach.
Four Kinds of Learning in One Agent-Oriented Environment
Authors: Nirenburg Sergei  , McShane Marjorie  , Beale Stephen  , English Jesse  , Catizone Roberta
Published: February 2025

This paper briefly describes four kinds of learning carried out by intelligent agents in a computational environment facilitating joint activities of people and software agents. The types of learning and the applications we draw examples from are: learning by being told and learning by experience, as illustrated through a virtual patient application; learning by reasoning, as illustrated through a clinician's advisor application; and learning by reading, as illustrated by an ontology enhancement application. The agents carrying out these types of learning are modeled using cognitive modeling strategies that show marked parallels with how humans seem to learn.
“Do you trust me or not?” – Trust games in agent societies
Authors: Figueiredo Rui  , Carmo João  , Prada Rui
Published: February 2025

Multi-agent simulation provides a way to explore results from social studies and provide hints on how these results scale. One particular class of studies that is interesting to explore are economic-related studies. We developed a multi-agent system that simulates an investment game and incorporates the results from economic-related social studies into the design of the agents. We analyzed how several factors, such as trust and reputation influence the outcome of the agents in terms of distribution of wealth and total generated money.
Probabilistic Logic with Conditional Independence Formulae
Authors: Ivanovska Magdalena  , Giese Martin
Published: February 2025

We investigate probabilistic propositional logic as a way of expressing and reasoning about uncertainty. In contrast to Bayesian networks, a logical approach can easily cope with incomplete information like probabilities that are missing or only known to lie in some interval. However, probabilistic propositional logic as described e.g. by Halpern [1], has no way of expressing conditional independence, which is important for compact specification in many cases. We define a logic with conditional independence formulae. We give an axiomatization which we show to be complete for the kind of inferences allowed by Bayesian networks, while still being suitable for reasoning under incomplete information.
Obligationes as Formal Dialogue Systems
Authors: Uckelman Sara L.
Published: February 2025

Formal Dialogue Systems (FDSs) model rule-based interaction between agents. Their conceptual roots go back to Hamblin's [11,12], which cites the medieval theory of obligationes as inspiration for his development of a formal system of argumentation. In an obligatio, two agents, Opponent and Respondent, engage in an alternating-move dialogue, where Respondent's actions are governed by certain rules, and the goal of the dialogue is establishing the consistency of a proposition. We implement obligationes in the formal dialogue system framework of [20] using Dynamic Epistemic Logic [26]. The result is a new type of inter-agent dialogue, consistency-checking, and analyzing obligationes in this way also sheds light on interpretational and historical questions concerning their use and purpose in medieval academia.
On-line ADL Recognition with Prior Knowledge
Authors: Ullberg Jonas  , Coradeschi Silvia  , Pecora Federico
Published: February 2025

This paper addresses the problem of recognizing activities of daily living. The novelty lies in the use of an existing knowledge base (ConceptNet) to introduce prior knowledge into the system in order to reduce the amount of learning required to deploy the system in a real environment. The use of household objects is central in the recognition of activities that are being performed, and we attach semantic meaning to both the objects and activities that are being recognized. The paper describes a framework which is specifically geared towards realizing activity recognition systems which leverage prior knowledge. A preliminary implementation of a neural network based recognition system built on this framework is shown, and the added value of prior knowledge is evaluated through the use of various data sets.
A Legal Decision Support Guide for Owners Corporation Cases
Authors: Condliffe Peter  , Abrahams Brooke  , Zeleznikow John
Published: February 2025

The paper describes the development of a legal decision support guide to relevant case law decisions for owners corporation cases in the state of Victoria, Australia. The rate of growth of owners corporations (also known as body corporate or strata title properties) has increased significantly in the last two decades. Because of this growth, and the need to manage a rapidly expanding population, the governance and management of these entities has become an important concern for government. Conflict and its management within them is an essential element of this concern. The Victorian legislation outlines a three-tiered process for resolving disputes. Cases that can't be settled through negotiation are often referred to the Victorian Civil and Administrative Tribunal (VCAT). Through our system we aim to provide legal decision support for relevant case law decisions determined by VCAT to help guide disputants through the grievance process.
Canonicalizing Complex Case Law Citations
Authors: van Opijnen Marc
Published: February 2025

Case law is cited by various types of identifiers: neutral citation numbers, vendor specific identifiers, triples of court name, judgment date and case number, in all possible combinations and spelling variants. Such diversity hinders the development of citation indexes, proper hyperlinking and statistical analysis. This paper discusses a solution to recognize, normalize and deduplicate case law citations in unstructured documents.
Spatial Ontology in Factored Statistical Machine Translation
Authors: Skadiņš Raivis
Published: February 2025

This paper presents a statistical phrase-based machine translation system which is enriched with semantic data coming from a spatial ontology. Paper presents the spatial ontology, how it is integrated in statistical machine translation system using factored models and how it is being evaluated using both automatic and human evaluation. Spatial information is added as a factor in both translation and language models. SOLIM spatial ontology language is used to implement ontology and to infer necessary knowledge for training statistical machine translation system. The machine translation system is based on Moses toolkit.
Combining Functional and Nonfunctional Attributes for Cost Driven Web Service Selection
Authors: Bonders Mārtiņš  , Grabis Jānis  , Kampars Jānis
Published: February 2025

Selection of appropriate web services is an important step in development of composite applications. Quality of Service (QoS) data characterizing nonfunctional properties of candidate web services are usually used in web service selection. However, functional characteristics, which are difficult to measure, are equally important. Quantitative evaluation of functional characteristics is possible in the case of development of composite decision-making applications. This paper elaborates a web service selection method, which accounts for both functional and nonfunctional characteristics of candidate web services. The functional characteristics are evaluated according to decision-making results yielded by the composite application. A linear programming model is used as the web service selection method and the cost of developing and operating the composite application is used as a selection metric. Application of the proposed web service selection method is demonstrated by developing a composite application for a vehicle routing problem, where web services are required to provide spatial data necessary for the decision-making algorithm. Experimental results show that accounting for functional characteristics substantially affects web service selection results.
Ontology-driven Development of Personalized Location Based Services
Authors: Haav Hele-Mai  , Kaljuvee Aivi  , Luts Martin  , Vajakas Toivo
Published: February 2025

Personalization is very important feature of any Location Base Service (LBS) as it improves its usability. The paper focuses a problem of development of personalized LBSs. In the paper, a novel approach based on ontology engineering is proposed to provide an intelligent (semantics-based) solution to personalization problem of LBS. The approach uses geospatial ontologies, ontology-based user profiling and multilingual output for personalization of services. The provided ontology-driven development framework for personalized LBS is evaluated by implementing the personalized reverse geo-coding service use case.
Parallel Bidirectional Dijkstra's Shortest Path Algorithm
Authors: Vaira Gintaras  , Kurasova Olga
Published: February 2025

This paper deals with Dijkstra's shortest path algorithm and with the possibilities of speeding-up this algorithm. This algorithm is a breadth-first-search algorithm. The search spreads circularly around the source node in order to find the shortest path from the source node to other nodes. Each following iteration is based on the results of the previous iteration, therefore parallelization of such an algorithm is complicated. The parallel Dijkstra algorithm, proposed in this paper, is based on the bidirectional Dijkstra algorithm and popular multicore technology. Such a technology enables to create a parallel algorithm based on the shared memory and most of the time for data synchronization thereby is saved. The proposed algorithm has been tested using the real road network data. The proposed parallel algorithm is almost 3 times faster than the standard Dijkstra algorithm.
On Views on Metamodels
Authors: Rencis Edgars
Published: February 2025

Several metamodels are often introduced when looking at the same fragment of the real world from different points of view. This process involves multiplying data to be instances of those metamodels thus enforcing the redundancy and complicating the maintenance. In this paper, a mechanism for defining (read only) views on arbitrary metamodels is presented. Having the mechanism, a user is allowed to work with the view metamodel and its instances by the means of a model transformation language while at the same time only instances of the base metamodel are kept physically in the memory. Thus, the proposed view definition mechanism does not introduce a redundancy of data. Also, the basic ideas of compiling model transformation programs from the view metamodel to the base metamodel are outlined here.
A Simple Model of Negotiation for Cooperative Updates on Database Schema Components
Authors: Hegner Stephen J.
Published: February 2025

Modern applications involving information systems often require the cooperation of several distinct users, and many models of such cooperation have arisen over the years. One way to model such situations is via a cooperative update on a database; that is, an update for which no single user has the necessary access rights, so that several users, each with distinct rights, must cooperate to achieve the desired goal. However, cooperative update mandates new ways of modelling and extending certain fundamentals of database systems. In this paper, such extensions are explored, using database schema components as the underlying model. The main contribution is an effective three-stage process for inter-component negotiation.