Creationism and evolution

In Tower of Babel, Robert Pennock wrote that “defenders of evolution would help their case immeasurably if they would reassure their audience that morality, purpose, and meaning are not lost by accepting the truth of evolution.” We first consider the thesis that the creationists’ movement exploits moral concerns to spread its ideas against the theory of evolution. We analyze their arguments and possible reasons why they are easily accepted. Creationists usually employ two contradictive strategies to expose the purported moral degradation that comes with accepting the theory of evolution. On the one hand they claim that evolutionary theory is immoral. On the other hand creationists think of evolutionary theory as amoral. Both objections come naturally in a monotheistic view. But we can find similar conclusions about the supposed moral aspects of evolution in non-religiously inspired discussions. Meanwhile, the creationism-evolution debate mainly focuses — understandably — on what constitutes good science. We consider the need for moral reassurance and analyze reassuring arguments from philosophers. Philosophers may stress that science does not prescribe and is therefore not immoral, but this reaction opens the door for the objection of amorality that evolution — as a naturalistic world view at least — supposedly endorses. We consider that the topic of morality and its relation to the acceptance of evolution may need more empirical research

Logic In Context: An essay on the contextual foundations of logical pluralism

The core pluralist thesis about logic, broadly construed, is the claim that two or more logics are correct. In this thesis I discuss a uniquely interesting variant of logical pluralism that I call logical contextualism. Roughly, the logical contextualists’ thought is that, for fixed values p and q, the statement “p entails q” and its cognates such as “q is a logical consequence of p” or “the argument from p to q is logically valid,” are true in some contexts and false in others. After developing a contextualist account of logical pluralism I proceed to examine implications that, if true, logical contextualism would have on discussions about reasonable disagreement among epistemic peers and on discussions about the aim and purpose of argumentation. I show that logical contextualism allows for the possibility of logically-based reasonable disagreements among epistemic peers. In the face of such disagreements there is no obligation to revise one’s belief, nor is there any obligation to degrade the peer status of the agent with whom one stands in disagreement. The possibility of logically-based reasonable disagreements, it will be argued, suggests a reconceptualization of the aims and purpose of argumentation. Most accounts of the purpose of argumentation hold that argumentation’s primary purpose is to achieve rational agreement on a contested issue. Such an agreement is thought to require that at least one of the parties in the argumentation change their beliefs or commitments. However, the existence of logically-based reasonable disagreements, I argue, implies that there are some argumentations that ought not to resolve with agreement. Therefore, rather than understanding argumentation as purely an effort to convince an opponent, or as a means to reach consensus, I claim that argumentation ought to be understood as an effort to gain a better understanding of divergent and perhaps irreconcilable perspectives

31th International Conference on Information Modelling and Knowledge Bases

Information modelling is becoming more and more important topic for researchers, designers, and users of information systems.The amount and complexity of information itself, the number of abstractionlevels of information, and the size of databases and knowledge bases arecontinuously growing. Conceptual modelling is one of the sub-areas ofinformation modelling. The aim of this conference is to bring together experts from different areas of computer science and other disciplines, who have a common interest in understanding and solving problems on information modelling and knowledge bases, as well as applying the results of research to practice. We also aim to recognize and study new areas on modelling and knowledge bases to which more attention should be paid. Therefore philosophy and logic, cognitive science, knowledge management, linguistics and management science are relevant areas, too. In the conference, there will be three categories of presentations, i.e. full papers, short papers and position papers

Foundations of Trusted Autonomy

Trusted Autonomy; Automation Technology; Autonomous Systems; Self-Governance; Trusted Autonomous Systems; Design of Algorithms and Methodologie

Asking and Answering

Questions are everywhere and the ubiquitous activities of asking and answering, as most human activities, are susceptible to failure - at least from time to time. This volume offers several current approaches to the systematic study of questions and the surrounding activities and works toward supporting and improving these activities. The contributors formulate general problems for a formal treatment of questions, investigate specific kinds of questions, compare different frameworks with regard to how they regulate the activities of asking and answering of questions, and situate these activities in a wider framework of cognitive/epistemic discourse. From the perspectives of logic, linguistics, epistemology, and philosophy of language emerges a report on the state of the art of the theory of questions

The Role of preferences in logic programming: nonmonotonic reasoning, user preferences, decision under uncertainty

Intelligent systems that assist users in fulfilling complex tasks need a concise and processable representation of incomplete and uncertain information. In order to be able to choose among different options, these systems also need a compact and processable representation of the concept of preference. Preferences can provide an effective way to choose the best solutions to a given problem. These solutions can represent the most plausible states of the world when we model incomplete information, the most satisfactory states of the world when we express user preferences, or optimal decisions when we make decisions under uncertainty. Several domains, such as, reasoning under incomplete and uncertain information, user preference modeling, and qualitative decision making under uncertainty, have benefited from advances on preference representation. In the literature, several symbolic approaches of nonclassical reasoning have been proposed. Among them, logic programming under answer set semantics offers a good compromise between symbolic representation and computation of knowledge and several extensions for handling preferences. Nevertheless, there are still some open issues to be considered in logic programming. In nonmonotonic reasoning, first, most approaches assume that exceptions to logic program rules are already specified. However, sometimes, it is possible to consider implicit preferences based on the specificity of the rules to handle incomplete information. Secondly, the joint handling of exceptions and uncertainty has received little attention: when information is uncertain, the selection of default rules can be a matter of explicit preferences and uncertainty. In user preference modeling, although existing logic programming specifications allow to express user preferences which depend both on incomplete and contextual information, in some applications, some preferences in some context may be more important than others. Furthermore, more complex preference expressions need to be supported. In qualitative decision making under uncertainty, existing logic programming-based methodologies for making decisions seem to lack a satisfactory handling of preferences and uncertainty. The aim of this dissertation is twofold: 1) to tackle the role played by preferences in logic programming from different perspectives, and 2) to contribute to this novel field by proposing several frameworks and methods able to address the above issues. To this end, we will first show how preferences can be used to select default rules in logic programs in an implicit and explicit way. In particular, we propose (i) a method for selecting logic program rules based on specificity, and (ii) a framework for selecting uncertain default rules based on explicit preferences and the certainty of the rules. Then, we will see how user preferences can be modeled and processed in terms of a logic program (iii) in order to manage user profiles in a context-aware system and (iv) in order to propose a framework for the specification of nested (non-flat) preference expressions. Finally, in the attempt to bridge the gap between logic programming and qualitative decision under uncertainty, (v) we propose a classical- and a possibilistic-based logic programming methodology to compute an optimal decision when uncertainty and preferences are matters of degrees.Els sistemes intel.ligents que assisteixen a usuaris en la realització de tasques complexes necessiten una representació concisa i formal de la informació que permeti un raonament nomonòton en condicions d’incertesa. Per a poder escollir entre les diferents opcions, aquests sistemes solen necessitar una representació del concepte de preferència. Les preferències poden proporcionar una manera efectiva de triar entre les millors solucions a un problema. Aquestes solucions poden representar els estats del món més plausibles quan es tracta de modelar informació incompleta, els estats del món més satisfactori quan expressem preferències de l’usuari, o decisions òptimes quan estem parlant de presa de decisió incorporant incertesa. L’ús de les preferències ha beneficiat diferents dominis, com, el raonament en presència d’informació incompleta i incerta, el modelat de preferències d’usuari, i la presa de decisió sota incertesa. En la literatura, s’hi troben diferents aproximacions al raonament no clàssic basades en una representació simbòlica de la informació. Entre elles, l’enfocament de programació lògica, utilitzant la semàntica de answer set, ofereix una bona aproximació entre representació i processament simbòlic del coneixement, i diferents extensions per gestionar les preferències. No obstant això, en programació lògica es poden identificar diferents problemes pel que fa a la gestió de les preferències. Per exemple, en la majoria d’enfocaments de raonament no-monòton s’assumeix que les excepcions a default rules d’un programa lògic ja estan expressades. Però de vegades es poden considerar preferències implícites basades en l’especificitat de les regles per gestionar la informació incompleta. A més, quan la informació és també incerta, la selecció de default rules pot dependre de preferències explícites i de la incertesa. En el modelatge de preferències del usuari, encara que els formalismes existents basats en programació lògica permetin expressar preferències que depenen d’informació contextual i incompleta, en algunes aplicacions, donat un context, algunes preferències poden ser més importants que unes altres. Per tant, resulta d’interès un llenguatge que permeti capturar preferències més complexes. En la presa de decisions sota incertesa, les metodologies basades en programació lògica creades fins ara no ofereixen una solució del tot satisfactòria pel que fa a la gestió de les preferències i la incertesa. L’objectiu d’aquesta tesi és doble: 1) estudiar el paper de les preferències en la programació lògica des de diferents perspectives, i 2) contribuir a aquesta jove àrea d’investigació proposant diferents marcs teòrics i mètodes per abordar els problemes anteriorment citats. Per a aquest propòsit veurem com les preferències es poden utilitzar de manera implícita i explícita per a la selecció de default rules proposant: (i) un mètode basat en l’especificitat de les regles, que permeti seleccionar regles en un programa lògic; (ii) un marc teòric per a la selecció de default rules incertes basat en preferències explícites i la incertesa de les regles. També veurem com les preferències de l’usuari poden ser modelades i processades usant un enfocament de programació lògica (iii) que suporti la creació d’un mecanisme de gestió dels perfils dels usuaris en un sistema amb reconeixement del context; (iv) que permeti proposar un marc teòric capaç d’expressar preferències amb fòrmules imbricades. Per últim, amb l’objectiu de disminuir la distància entre programació lògica i la presa de decisió amb incertesa proposem (v) una metodologia basada en programació lògica clàssica i en una extensió de la programació lògica que incorpora lògica possibilística per modelar un problema de presa de decisions i per inferir una decisió òptima.Los sistemas inteligentes que asisten a usuarios en tareas complejas necesitan una representación concisa y procesable de la información que permita un razonamiento nomonótono e incierto. Para poder escoger entre las diferentes opciones, estos sistemas suelen necesitar una representación del concepto de preferencia. Las preferencias pueden proporcionar una manera efectiva para elegir entre las mejores soluciones a un problema. Dichas soluciones pueden representar los estados del mundo más plausibles cuando hablamos de representación de información incompleta, los estados del mundo más satisfactorios cuando hablamos de preferencias del usuario, o decisiones óptimas cuando estamos hablando de toma de decisión con incertidumbre. El uso de las preferencias ha beneficiado diferentes dominios, como, razonamiento en presencia de información incompleta e incierta, modelado de preferencias de usuario, y toma de decisión con incertidumbre. En la literatura, distintos enfoques simbólicos de razonamiento no clásico han sido creados. Entre ellos, la programación lógica con la semántica de answer set ofrece un buen acercamiento entre representación y procesamiento simbólico del conocimiento, y diferentes extensiones para manejar las preferencias. Sin embargo, en programación lógica se pueden identificar diferentes problemas con respecto al manejo de las preferencias. Por ejemplo, en la mayoría de enfoques de razonamiento no-monótono se asume que las excepciones a default rules de un programa lógico ya están expresadas. Pero, a veces se pueden considerar preferencias implícitas basadas en la especificidad de las reglas para manejar la información incompleta. Además, cuando la información es también incierta, la selección de default rules pueden depender de preferencias explícitas y de la incertidumbre. En el modelado de preferencias, aunque los formalismos existentes basados en programación lógica permitan expresar preferencias que dependen de información contextual e incompleta, in algunas aplicaciones, algunas preferencias en un contexto puede ser más importantes que otras. Por lo tanto, un lenguaje que permita capturar preferencias más complejas es deseable. En la toma de decisiones con incertidumbre, las metodologías basadas en programación lógica creadas hasta ahora no ofrecen una solución del todo satisfactoria al manejo de las preferencias y la incertidumbre. El objectivo de esta tesis es doble: 1) estudiar el rol de las preferencias en programación lógica desde diferentes perspectivas, y 2) contribuir a esta joven área de investigación proponiendo diferentes marcos teóricos y métodos para abordar los problemas anteriormente citados. Para este propósito veremos como las preferencias pueden ser usadas de manera implícita y explícita para la selección de default rules proponiendo: (i) un método para seleccionar reglas en un programa basado en la especificad de las reglas; (ii) un marco teórico para la selección de default rules basado en preferencias explícitas y incertidumbre. También veremos como las preferencias del usuario pueden ser modeladas y procesadas usando un enfoque de programación lógica (iii) para crear un mecanismo de manejo de los perfiles de los usuarios en un sistema con reconocimiento del contexto; (iv) para crear un marco teórico capaz de expresar preferencias con formulas anidadas. Por último, con el objetivo de disminuir la distancia entre programación lógica y la toma de decisión con incertidumbre proponemos (v) una metodología para modelar un problema de toma de decisiones y para inferir una decisión óptima usando un enfoque de programación lógica clásica y uno de programación lógica extendida con lógica posibilística.Sistemi intelligenti, destinati a fornire supporto agli utenti in processi decisionali complessi, richiedono una rappresentazione dell’informazione concisa, formale e che permetta di ragionare in maniera non monotona e incerta. Per poter scegliere tra le diverse opzioni, tali sistemi hanno bisogno di disporre di una rappresentazione del concetto di preferenza altrettanto concisa e formale. Le preferenze offrono una maniera efficace per scegliere le miglior soluzioni di un problema. Tali soluzioni possono rappresentare gli stati del mondo più credibili quando si tratta di ragionamento non monotono, gli stati del mondo più soddisfacenti quando si tratta delle preferenze degli utenti, o le decisioni migliori quando prendiamo una decisione in condizioni di incertezza. Diversi domini come ad esempio il ragionamento non monotono e incerto, la strutturazione del profilo utente, e i modelli di decisione in condizioni d’incertezza hanno tratto beneficio dalla rappresentazione delle preferenze. Nella bibliografia disponibile si possono incontrare diversi approcci simbolici al ragionamento non classico. Tra questi, la programmazione logica con answer set semantics offre un buon compromesso tra rappresentazione simbolica e processamento dell’informazione, e diversi estensioni per la gestione delle preferenze sono state proposti in tal senso. Nonostante ció, nella programmazione logica esistono ancora delle problematiche aperte. Prima di tutto, nella maggior parte degli approcci al ragionamento non monotono, si suppone che nel programma le eccezioni alle regole siano già specificate. Tuttavia, a volte per trattare l’informazione incompleta è possibile prendere in considerazione preferenze implicite basate sulla specificità delle regole. In secondo luogo, la gestione congiunta di eccezioni e incertezza ha avuto scarsa attenzione: quando l’informazione è incerta, la scelta di default rule può essere una questione di preferenze esplicite e d’incertezza allo stesso tempo. Nella creazione di preferenze dell’utente, anche se le specifiche di programmazione logica esistenti permettono di esprimere preferenze che dipendono sia da un’informazione incompleta che da una contestuale, in alcune applicazioni talune preferenze possono essere più importanti di altre, o espressioni più complesse devono essere supportate. In un processo decisionale con incertezza, le metodologie basate sulla programmazione logica viste sinora, non offrono una gestione soddisfacente delle preferenze e dell’incertezza. Lo scopo di questa dissertazione è doppio: 1) chiarire il ruolo che le preferenze giocano nella programmazione logica da diverse prospettive e 2) contribuire proponendo in questo nuovo settore di ricerca, diversi framework e metodi in grado di affrontare le citate problematiche. Per prima cosa, dimostreremo come le preferenze possono essere usate per selezionare default rule in un programma in maniera implicita ed esplicita. In particolare proporremo: (i) un metodo per la selezione delle regole di un programma logico basato sulla specificità dell’informazione; (ii) un framework per la selezione di default rule basato sulle preferenze esplicite e sull’incertezza associata alle regole del programma. Poi, vedremo come le preferenze degli utenti possono essere modellate attraverso un programma logico, (iii) per creare il profilo dell’utente in un sistema context-aware, e (iv) per proporre un framework che supporti la definizione di preferenze complesse. Infine, per colmare le lacune in programmazione logica applicata a un processo di decisione con incertezza (v) proporremo una metodologia basata sulla programmazione logica classica e una metodologia basata su un’estensione della programmazione logica con logica possibilistica

Abstract book : 25th IVR World Congress of Philosophy of Law and Social Philosophy ; law, science, technology ; 15 – 20 August 2011, Frankfurt am Main, Germany

On behalf of myself and my colleagues Professor Dr. Klaus Günther and Professor Dr. Lorenz Schulz, it is my great pleasure to welcome you to the 25th World Congress of the International Association for Philosophy of Law and Social Philosophy (IVR) in Frankfurt am Main. ...Auch im Namen meiner Frankfurter Kollegen Prof. Dr. Klaus Günther und Prof. Dr. Lorenz Schulz möchte ich Sie zu dem 25. Weltkongress der Internationalen Vereinigung für Rechts- und Sozialphilosophie (IVR) in Frankfurt am Main sehr herzlich begrüßen. ..

The Pandemic of Argumentation

This open access book addresses communicative aspects of the current COVID-19 pandemic as well as the epidemic of misinformation from the perspective of argumentation theory. Argumentation theory is uniquely placed to understand and account for the challenges of public reason as expressed through argumentative discourse. The book thus focuses on the extent to which the forms, norms and functions of public argumentation have changed in the face of the COVID-19 pandemic. This question is investigated along the three main research lines of the COST Action project CA 17132: European network for Argumentation and Public PoLicY analysis (APPLY): descriptive, normative, and prescriptive. The volume offers a broad range of contributions which treat argumentative phenomena that are directly related to the changes in public discourse in the wake of the outburst of COVID-19. The volume additionally places particular emphasis on expert argumentation, given (i) the importance expert discourse has had over the last two years, and (ii) the challenges that expert argumentation has faced in the public sphere as a result of scientific uncertainty and widespread misinformation. Contributions are divided into three groups, which (i) examine various features and aspects of public and institutional discourse about the COVID-19 pandemic, (ii) scrutinize the way health policies have been discussed, debated, attacked and defended in the public sphere, and (iii) consider a range of proposals meant to improve the quality of public discourse, and public deliberation in particular, in such a way that concrete proposals for argumentative literacy will be brought to light. Overall, this volume constitutes a timely inquiry into all things argumentative in pandemic discourse. This volume is of interest to a broad readership including philosophers, linguists, communication and legal scholars, and members of the wider public who seek to better understand the discourse surrounding communicative phenomena in times of crisis. COST (European Cooperation in Science and Technology) is a funding organisation for research and innovation networks. For more information: www.cost.e

The Pandemic of Argumentation

This open access book addresses communicative aspects of the current COVID-19 pandemic as well as the epidemic of misinformation from the perspective of argumentation theory. Argumentation theory is uniquely placed to understand and account for the challenges of public reason as expressed through argumentative discourse. The book thus focuses on the extent to which the forms, norms and functions of public argumentation have changed in the face of the COVID-19 pandemic. This question is investigated along the three main research lines of the COST Action project CA 17132: European network for Argumentation and Public PoLicY analysis (APPLY): descriptive, normative, and prescriptive. The volume offers a broad range of contributions which treat argumentative phenomena that are directly related to the changes in public discourse in the wake of the outburst of COVID-19. The volume additionally places particular emphasis on expert argumentation, given (i) the importance expert discourse has had over the last two years, and (ii) the challenges that expert argumentation has faced in the public sphere as a result of scientific uncertainty and widespread misinformation. Contributions are divided into three groups, which (i) examine various features and aspects of public and institutional discourse about the COVID-19 pandemic, (ii) scrutinize the way health policies have been discussed, debated, attacked and defended in the public sphere, and (iii) consider a range of proposals meant to improve the quality of public discourse, and public deliberation in particular, in such a way that concrete proposals for argumentative literacy will be brought to light. Overall, this volume constitutes a timely inquiry into all things argumentative in pandemic discourse. This volume is of interest to a broad readership including philosophers, linguists, communication and legal scholars, and members of the wider public who seek to better understand the discourse surrounding communicative phenomena in times of crisis. COST (European Cooperation in Science and Technology) is a funding organisation for research and innovation networks. For more information: www.cost.e