Hierarchical Task Network Planning with Common-Sense Reasoning for Multiple-People Behaviour Analysis

Safety on public transport is a major concern for the relevant authorities. We
address this issue by proposing an automated surveillance platform which combines data from video, infrared and pressure sensors. Data homogenisation and integration is achieved by a distributed architecture based on communication middleware that resolves interconnection issues, thereby enabling data modelling. A common-sense knowledge base models and encodes knowledge about public-transport platforms and the actions and activities of passengers. Trajectory data from passengers is modelled as a time-series of human activities. Common-sense knowledge and rules are then applied to detect inconsistencies or errors in the data interpretation. Lastly, the rationality that characterises human behaviour is also captured here through a bottom-up Hierarchical Task Network planner that, along with common-sense, corrects misinterpretations to explain passenger behaviour. The system is validated using a simulated bus saloon scenario as a case-study. Eighteen video sequences were recorded with up to six passengers. Four metrics were used to evaluate performance. The system, with an accuracy greater than 90% for each of the four metrics, was found to outperform a rule-base system and a system containing planning alone.

Reasoning about change over time: Actions, events and their effects

This paper presents a new formalism for reasoning about change over time. The formalism derives a clean separation between the notion of states and situations. It allows more flexible temporal causal relationships than do other formalisms for reasoning about causal change, such as the situation calculus and the event calculus. It includes effects that start during, immediately after, or some time after their causes, and which end before, simultaneously with, or after their causes. A formal distinction between actions, action-types and events is proposed, which allows the expression of common-sense causal laws at high level. It is shown how these laws can be used to deduce state change over time at low level, when events occur under certain preconditions hold. Two problems that beset most interval-based temporal systems, i.e., the so-called dividing instant problem and intermingling problem, are absent from the formalism.

Inteligência artificial aplicada à Zootecnia

Os sistemas biológicos são surpreendentemente flexíveis pra processar informação proveniente do mundo real. Alguns organismos biológicos possuem uma unidade central de processamento denominada de cérebro. O cérebro humano consiste de 10(11) neurônios e realiza processamento inteligente de forma exata e subjetiva. A Inteligência Artificial (IA) tenta trazer para o mundo da computação digital a heurística dos sistemas biológicos de várias maneiras, mas, ainda resta muito para que isso seja concretizado. No entanto, algumas técnicas como Redes neurais artificiais e lógica fuzzy tem mostrado efetivas para resolver problemas complexos usando a heurística dos sistemas biológicos. Recentemente o numero de aplicação dos métodos da IA em sistemas zootécnicos tem aumentado significativamente. O objetivo deste artigo é explicar os princípios básicos da resolução de problemas usando heurística e demonstrar como a IA pode ser aplicada para construir um sistema especialista para resolver problemas na área de zootecnia.

Formalizing defeasible argumentation using a labeled deductive system

In the last years there has been an increasing demand of a variety of logical systems, prompted mostly by applications of logic in AI, logic programming and other related areas. Labeled Deductive Systems (LDS) were developed as a flexible methodology to formalize such a kind of complex logical systems. In the last decade, defeasible argumentation has proven to be a confluence point for many approaches to formalizing commonsense reasoning. Different formalisms have been developed, many of them sharing common features. This paper presents a formalization of an LDS for defensible argumentation, in which the main issues concerning defeasible argumentation are captured within a unified logical framework. The proposed framework is defined in two stages. First, defeasible inference will be formalized by characterizing an argumentative LDS. That system will be then extended in order to capture conflict among arguments using a dialectical approach. We also present some logical properties emerging from the proposed framework, discussing also its semantical characterization.

One reason, several logics

Humans have used arguments for defending or refuting statements long before the creation of logic as a specialized discipline. This can be interpreted as the fact that an intuitive notion of "logical consequence" or a psychic disposition to articulate reasoning according to this pattern is present in common sense, and logic simply aims at describing and codifying the features of this spontaneous capacity of human reason. It is well known, however, that several arguments easily accepted by common sense are actually "logical fallacies", and this indicates that logic is not just a descriptive, but also a prescriptive or normative enterprise, in which the notion of logical consequence is defined in a precise way and then certain rules are established in order to maintain the discourse in keeping with this notion. Yet in the justification of the correctness and adequacy of these rules commonsense reasoning must necessarily be used, and in such a way its foundational role is recognized. Moreover, it remains also true that several branches and forms of logic have been elaborated precisely in order to reflect the structural features of correct argument used in different fields of human reasoning and yet insufficiently mirrored by the most familiar logical formalisms.

La filosofia di Hans-Georg Gadamer e il problema del disagio della modernità. Ermeneutica, estetica, etica e politica

L’ermeneutica filosofica di Hans-Georg Gadamer – indubbiamente uno dei capisaldi del pensiero novecentesco – rappresenta una filosofia molto composita, sfaccettata e articolata, per così dire formata da una molteplicità di dimensioni diverse che si intrecciano l’una con l’altra. Ciò risulta evidente già da un semplice sguardo alla composizione interna della sua opera principale, Wahrheit und Methode (1960), nella quale si presenta una teoria del comprendere che prende in esame tre differenti dimensioni dell’esperienza umana – arte, storia e linguaggio – ovviamente concepite come fondamentalmente correlate tra loro. Ma questo quadro d’insieme si complica notevolmente non appena si prendano in esame perlomeno alcuni dei numerosi contributi che Gadamer ha scritto e pubblicato prima e dopo il suo opus magnum: contributi che testimoniano l’importante presenza nel suo pensiero di altre tematiche. Di tale complessità, però, non sempre gli interpreti di Gadamer hanno tenuto pienamente conto, visto che una gran parte dei contributi esegetici sul suo pensiero risultano essenzialmente incentrati sul capolavoro del 1960 (ed in particolare sui problemi della legittimazione delle Geisteswissenschaften), dedicando invece minore attenzione agli altri percorsi che egli ha seguito e, in particolare, alla dimensione propriamente etica e politica della sua filosofia ermeneutica. Inoltre, mi sembra che non sempre si sia prestata la giusta attenzione alla fondamentale unitarietà – da non confondere con una presunta “sistematicità”, da Gadamer esplicitamente respinta – che a dispetto dell’indubbia molteplicità ed eterogeneità del pensiero gadameriano comunque vige al suo interno. La mia tesi, dunque, è che estetica e scienze umane, filosofia del linguaggio e filosofia morale, dialogo con i Greci e confronto critico col pensiero moderno, considerazioni su problematiche antropologiche e riflessioni sulla nostra attualità sociopolitica e tecnoscientifica, rappresentino le diverse dimensioni di un solo pensiero, le quali in qualche modo vengono a convergere verso un unico centro. Un centro “unificante” che, a mio avviso, va individuato in quello che potremmo chiamare il disagio della modernità. In altre parole, mi sembra cioè che tutta la riflessione filosofica di Gadamer, in fondo, scaturisca dalla presa d’atto di una situazione di crisi o disagio nella quale si troverebbero oggi il nostro mondo e la nostra civiltà. Una crisi che, data la sua profondità e complessità, si è per così dire “ramificata” in molteplici direzioni, andando ad investire svariati ambiti dell’esistenza umana. Ambiti che pertanto vengono analizzati e indagati da Gadamer con occhio critico, cercando di far emergere i principali nodi problematici e, alla luce di ciò, di avanzare proposte alternative, rimedi, “correttivi” e possibili soluzioni. A partire da una tale comprensione di fondo, la mia ricerca si articola allora in tre grandi sezioni dedicate rispettivamente alla pars destruens dell’ermeneutica gadameriana (prima e seconda sezione) ed alla sua pars costruens (terza sezione). Nella prima sezione – intitolata Una fenomenologia della modernità: i molteplici sintomi della crisi – dopo aver evidenziato come buona parte della filosofia del Novecento sia stata dominata dall’idea di una crisi in cui verserebbe attualmente la civiltà occidentale, e come anche l’ermeneutica di Gadamer possa essere fatta rientrare in questo discorso filosofico di fondo, cerco di illustrare uno per volta quelli che, agli occhi del filosofo di Verità e metodo, rappresentano i principali sintomi della crisi attuale. Tali sintomi includono: le patologie socioeconomiche del nostro mondo “amministrato” e burocratizzato; l’indiscriminata espansione planetaria dello stile di vita occidentale a danno di altre culture; la crisi dei valori e delle certezze, con la concomitante diffusione di relativismo, scetticismo e nichilismo; la crescente incapacità a relazionarsi in maniera adeguata e significativa all’arte, alla poesia e alla cultura, sempre più degradate a mero entertainment; infine, le problematiche legate alla diffusione di armi di distruzione di massa, alla concreta possibilità di una catastrofe ecologica ed alle inquietanti prospettive dischiuse da alcune recenti scoperte scientifiche (soprattutto nell’ambito della genetica). Una volta delineato il profilo generale che Gadamer fornisce della nostra epoca, nella seconda sezione – intitolata Una diagnosi del disagio della modernità: il dilagare della razionalità strumentale tecnico-scientifica – cerco di mostrare come alla base di tutti questi fenomeni egli scorga fondamentalmente un’unica radice, coincidente peraltro a suo giudizio con l’origine stessa della modernità. Ossia, la nascita della scienza moderna ed il suo intrinseco legame con la tecnica e con una specifica forma di razionalità che Gadamer – facendo evidentemente riferimento a categorie interpretative elaborate da Max Weber, Martin Heidegger e dalla Scuola di Francoforte – definisce anche «razionalità strumentale» o «pensiero calcolante». A partire da una tale visione di fondo, cerco quindi di fornire un’analisi della concezione gadameriana della tecnoscienza, evidenziando al contempo alcuni aspetti, e cioè: primo, come l’ermeneutica filosofica di Gadamer non vada interpretata come una filosofia unilateralmente antiscientifica, bensì piuttosto come una filosofia antiscientista (il che naturalmente è qualcosa di ben diverso); secondo, come la sua ricostruzione della crisi della modernità non sfoci mai in una critica “totalizzante” della ragione, né in una filosofia della storia pessimistico-negativa incentrata sull’idea di un corso ineluttabile degli eventi guidato da una razionalità “irrazionale” e contaminata dalla brama di potere e di dominio; terzo, infine, come la filosofia di Gadamer – a dispetto delle inveterate interpretazioni che sono solite scorgervi un pensiero tradizionalista, autoritario e radicalmente anti-illuminista – non intenda affatto respingere l’illuminismo scientifico moderno tout court, né rinnegarne le più importanti conquiste, ma più semplicemente “correggerne” alcune tendenze e recuperare una nozione più ampia e comprensiva di ragione, in grado di render conto anche di quegli aspetti dell’esperienza umana che, agli occhi di una razionalità “limitata” come quella scientista, non possono che apparire come meri residui di irrazionalità. Dopo aver così esaminato nelle prime due sezioni quella che possiamo definire la pars destruens della filosofia di Gadamer, nella terza ed ultima sezione – intitolata Una terapia per la crisi della modernità: la riscoperta dell’esperienza e del sapere pratico – passo quindi ad esaminare la sua pars costruens, consistente a mio giudizio in un recupero critico di quello che egli chiama «un altro tipo di sapere». Ossia, in un tentativo di riabilitazione di tutte quelle forme pre- ed extra-scientifiche di sapere e di esperienza che Gadamer considera costitutive della «dimensione ermeneutica» dell’esistenza umana. La mia analisi della concezione gadameriana del Verstehen e dell’Erfahrung – in quanto forme di un «sapere pratico (praktisches Wissen)» differente in linea di principio da quello teorico e tecnico – conduce quindi ad un’interpretazione complessiva dell’ermeneutica filosofica come vera e propria filosofia pratica. Cioè, come uno sforzo di chiarificazione filosofica di quel sapere prescientifico, intersoggettivo e “di senso comune” effettivamente vigente nella sfera della nostra Lebenswelt e della nostra esistenza pratica. Ciò, infine, conduce anche inevitabilmente ad un’accentuazione dei risvolti etico-politici dell’ermeneutica di Gadamer. In particolare, cerco di esaminare la concezione gadameriana dell’etica – tenendo conto dei suoi rapporti con le dottrine morali di Platone, Aristotele, Kant e Hegel – e di delineare alla fine un profilo della sua ermeneutica filosofica come filosofia del dialogo, della solidarietà e della libertà.

Conservation GIS: Ontology and spatial reasoning for commonsense knowledge.

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Using Analogy to Acquire Commonsense Knowledge from Human Contributors

The goal of the work reported here is to capture the commonsense knowledge of non-expert human contributors. Achieving this goal will enable more intelligent human-computer interfaces and pave the way for computers to reason about our world. In the domain of natural language processing, it will provide the world knowledge much needed for semantic processing of natural language. To acquire knowledge from contributors not trained in knowledge engineering, I take the following four steps: (i) develop a knowledge representation (KR) model for simple assertions in natural language, (ii) introduce cumulative analogy, a class of nearest-neighbor based analogical reasoning algorithms over this representation, (iii) argue that cumulative analogy is well suited for knowledge acquisition (KA) based on a theoretical analysis of effectiveness of KA with this approach, and (iv) test the KR model and the effectiveness of the cumulative analogy algorithms empirically. To investigate effectiveness of cumulative analogy for KA empirically, Learner, an open source system for KA by cumulative analogy has been implemented, deployed, and evaluated. (The site "1001 Questions," is available at http://teach-computers.org/learner.html). Learner acquires assertion-level knowledge by constructing shallow semantic analogies between a KA topic and its nearest neighbors and posing these analogies as natural language questions to human contributors. Suppose, for example, that based on the knowledge about "newspapers" already present in the knowledge base, Learner judges "newspaper" to be similar to "book" and "magazine." Further suppose that assertions "books contain information" and "magazines contain information" are also already in the knowledge base. Then Learner will use cumulative analogy from the similar topics to ask humans whether "newspapers contain information." Because similarity between topics is computed based on what is already known about them, Learner exhibits bootstrapping behavior --- the quality of its questions improves as it gathers more knowledge. By summing evidence for and against posing any given question, Learner also exhibits noise tolerance, limiting the effect of incorrect similarities. The KA power of shallow semantic analogy from nearest neighbors is one of the main findings of this thesis. I perform an analysis of commonsense knowledge collected by another research effort that did not rely on analogical reasoning and demonstrate that indeed there is sufficient amount of correlation in the knowledge base to motivate using cumulative analogy from nearest neighbors as a KA method. Empirically, evaluating the percentages of questions answered affirmatively, negatively and judged to be nonsensical in the cumulative analogy case compares favorably with the baseline, no-similarity case that relies on random objects rather than nearest neighbors. Of the questions generated by cumulative analogy, contributors answered 45% affirmatively, 28% negatively and marked 13% as nonsensical; in the control, no-similarity case 8% of questions were answered affirmatively, 60% negatively and 26% were marked as nonsensical.

Learning Commonsense Categorical Knowledge in a Thread Memory System

If we are to understand how we can build machines capable of broad purpose learning and reasoning, we must first aim to build systems that can represent, acquire, and reason about the kinds of commonsense knowledge that we humans have about the world. This endeavor suggests steps such as identifying the kinds of knowledge people commonly have about the world, constructing suitable knowledge representations, and exploring the mechanisms that people use to make judgments about the everyday world. In this work, I contribute to these goals by proposing an architecture for a system that can learn commonsense knowledge about the properties and behavior of objects in the world. The architecture described here augments previous machine learning systems in four ways: (1) it relies on a seven dimensional notion of context, built from information recently given to the system, to learn and reason about objects' properties; (2) it has multiple methods that it can use to reason about objects, so that when one method fails, it can fall back on others; (3) it illustrates the usefulness of reasoning about objects by thinking about their similarity to other, better known objects, and by inferring properties of objects from the categories that they belong to; and (4) it represents an attempt to build an autonomous learner and reasoner, that sets its own goals for learning about the world and deduces new facts by reflecting on its acquired knowledge. This thesis describes this architecture, as well as a first implementation, that can learn from sentences such as ``A blue bird flew to the tree'' and ``The small bird flew to the cage'' that birds can fly. One of the main contributions of this work lies in suggesting a further set of salient ideas about how we can build broader purpose commonsense artificial learners and reasoners.

Bio-QA-GNN: Reasoning with Language Models and Knowledge Graphs for Interpretable Biomedical Question Answering

Nowadays the idea of injecting world or domain-specific structured knowledge into pre-trained language models (PLMs) is becoming an increasingly popular approach for solving problems such as biases, hallucinations, huge architectural sizes, and explainability lack—critical for real-world natural language processing applications in sensitive fields like bioinformatics. One recent work that has garnered much attention in Neuro-symbolic AI is QA-GNN, an end-to-end model for multiple-choice open-domain question answering (MCOQA) tasks via interpretable text-graph reasoning. Unlike previous publications, QA-GNN mutually informs PLMs and graph neural networks (GNNs) on top of relevant facts retrieved from knowledge graphs (KGs). However, taking a more holistic view, existing PLM+KG contributions mainly consider commonsense benchmarks and ignore or shallowly analyze performances on biomedical datasets. This thesis start from a propose of a deep investigation of QA-GNN for biomedicine, comparing existing or brand-new PLMs, KGs, edge-aware GNNs, preprocessing techniques, and initialization strategies. By combining the insights emerged in DISI's research, we introduce Bio-QA-GNN that include a KG. Working with this part has led to an improvement in state-of-the-art of MCOQA model on biomedical/clinical text, largely outperforming the original one (+3.63\% accuracy on MedQA). Our findings also contribute to a better understanding of the explanation degree allowed by joint text-graph reasoning architectures and their effectiveness on different medical subjects and reasoning types. Codes, models, datasets, and demos to reproduce the results are freely available at: \url{https://github.com/disi-unibo-nlp/bio-qagnn}.

Improving Critical Thinking and Clinical Reasoning With a Continuing Education Course

Background: Continuing education courses related to critical thinking and clinical reasoning are needed to improve the accuracy of diagnosis. Method: This study evaluated a 4-day, 16-hour continuing education course conducted in Brazil. Thirty-nine nurses completed a pretest and a posttest consisting of two written case studies designed to measure the accuracy of nurses` diagnoses. Results: There were significant differences in accuracy from pretest to posttest for case 1 (p = .008) and case 2 (p = .042) and overall (p = .001). Conclusion: Continuing education courses should be implemented to improve the accuracy of nurses` diagnoses. J Contin Educ Nurs 2009;40(3):121-127.

Equational Reasoning as a Tool for Data Analysis

A combination of deductive reasoning, clustering, and inductive learning is given as an example of a hybrid system for exploratory data analysis. Visualization is replaced by a dialogue with the data.

The frontal assessment battery (FAB) reveals neurocognitive dysfunction in substance-dependent individuals in distinct executive domains: Abstract reasoning, motor programming, and cognitive flexibility

Substance-dependence is highly associated with executive cognitive function (ECF) impairments. However. considering that it is difficult to assess ECF clinically, the aim of the present study was to examine the feasibility of a brief neuropsychological tool (the Frontal Assessment Battery FAB) to detect specific ECF impairments in a sample of substance-dependent individuals (SDI). Sixty-two subjects participated in this study. Thirty DSM-IV-diagnosed SDI, after 2 weeks of abstinence, and 32 healthy individuals (control group) were evaluated with FAD and other ECF-related tasks: digits forward (DF), digits backward (DB), Stroop Color Word Test (SCWT), and Wisconsin Card Sorting Test (WCST). SDI did not differ from the control group on sociodemographic variables or IQ. However, SDI performed below the controls in OF, DB, and FAB. The SDI were cognitively impaired in 3 of the 6 cognitive domains assessed by the FAB: abstract reasoning, motor programming, and cognitive flexibility. The FAB correlated with DF, SCWT, and WCST. In addition, some neuropsychological measures were correlated with the amount of alcohol, cannabis, and cocaine use. In conclusion, SDI performed more poorly than the comparison group on the FAB and the FAB`s results were associated with other ECF-related tasks. The results suggested a negative impact of alcohol, cannabis, and cocaine use on the ECF. The FAB may be useful in assisting professionals as an instrument to screen for ECF-related deficits in SDI. (C) 2010 Elsevier Ltd. All rights reserved.