Planning multisentential English text using communicative acts

The goal of this research is to develop explanation presentation mechanisms for knowledge based systems which enable them to define domain terminology and concepts, narrate events, elucidate plans, processes, or propositions and argue to support a claim or advocate action. This requires the development of devices which select, structure, order and then linguistically realize explanation content as coherent and cohesive English text. With the goal of identifying generic explanation presentation strategies, a wide range of naturally occurring texts were analyzed with respect to their communicative sttucture, function, content and intended effects on the reader. This motivated an integrated theory of communicative acts which characterizes text at the level of rhetorical acts (e.g., describe, define, narrate), illocutionary acts (e.g., inform, request), and locutionary acts (e.g., ask, command). Taken as a whole, the identified communicative acts characterize the structure, content and intended effects of four types of text: description, narration, exposition, argument. These text types have distinct effects such as getting the reader to know about entities, to know about events, to understand plans, processes, or propositions, or to believe propositions or want to perform actions. In addition to identifying the communicative function and effect of text at multiple levels of abstraction, this dissertation details a tripartite theory of focus of attention (discourse focus, temporal focus, and spatial focus) which constrains the planning and linguistic realization of text. To test the integrated theory of communicative acts and tripartite theory of focus of attention, a text generation system TEXPLAN (Textual EXplanation PLANner) was implemented that plans and linguistically realizes multisentential and multiparagraph explanations from knowledge based systems. The communicative acts identified during text analysis were formalized as over sixty compositional and (in some cases) recursive plan operators in the library of a hierarchical planner. Discourse, temporal, and spatial focus models were implemented to track and use attentional information to guide the organization and realization of text. Because the plan operators distinguish between the communicative function (e.g., argue for a proposition) and the expected effect (e.g., the reader believes the proposition) of communicative acts, the system is able to construct a discourse model of the structure and function of its textual responses as well as a user model of the expected effects of its responses on the reader's knowledge, beliefs, and desires. The system uses both the discourse model and user model to guide subsequent utterances. To test its generality, the system was interfaced to a variety of domain applications including a neuropsychological diagnosis system, a mission planning system, and a knowledge based mission simulator. The system produces descriptions, narrations, expositions, and arguments from these applications, thus exhibiting a broader range of rhetorical coverage than previous text generation systems

The Crux of Crucial Experiments: Duhem's Problems and Inference to the Best Explanation

Going back at least to Duhem, there is a tradition of thinking that crucial experiments are impossible in science. I analyse Duhem's arguments and show that they are based on the excessively strong assumption that only deductive reasoning is permissible in experimental science. This opens the possibility that some principle of inductive inference could provide a sufficient reason for preferring one among a group of hypotheses on the basis of an appropriately controlled experiment. To be sure, there are analogues to Duhem's problems that pertain to inductive inference. Using a famous experiment from the history of molecular biology as an example, I show that an experimentalist version of inference to the best explanation (IBE) does a better job in handling these problems than other accounts of scientific inference. Furthermore, I introduce a concept of experimental mechanism and show that it can guide inferences from data within an IBE-based framework for induction. Introduction Duhem on the Logic of Crucial Experiments ‘The Most Beautiful Experiment in Biology' Why Not Simple Elimination? Severe Testing An Experimentalist Version of IBE 6.1Physiological and experimental mechanisms 6.2Explaining the data 6.3IBE and the problem of untested auxiliaries 6.4IBE-turtles all the way down Van Fraassen's ‘Bad Lot' Argument IBE and Bayesianism Conclusion

AUTOMATIC GENERATION OF INTELLIGENT TUTORING CAPABILITIES VIA EDUCATIONAL DATA MINING

Intelligent Tutoring Systems (ITSs) that adapt to an individual student’s needs have shown significant improvement in achievement over non-adaptive instruction (Murray 1999). This improvement occurs due to the individualized instruction and feedback that an ITS provides. In order to achieve the benefits that ITSs provide, we must find a way to simplify their creation. Therefore, we have created methods that can use data to automatically generate hints to adapt computer-aided instruction to help individual students. Our MDP method uses data from past student attempts on given problem to generate a graph of likely paths students take to solve a problem. These graphs can be used by educators to clearly understand how students are solving the problem or to provide hints for new students working the problem by pointing them down a successful path to solve the problem. We introduce the Hint Factory which is an implementation of the MDP method in an actual tutor used to solve logic proofs. We show that the Hint Factory can successfully help students solve more problems and show that students with access to hints are more likely to attempt harder problems than those without hints. In addition, we have enhanced the MDP method by creating a “utility” function that allows MDPs to be created when the problem solution may not be labeled. We show that this utility function performs as well as the traditional MDP method for our logic problems. We also created a Bayesian Knowledge Base to combine the information from multiple MDPs into a single corpus that will allow the Hint Factory to provide hints on new problems where no student data exists. Finally, we applied the MDP method to create models for other domains, including Stoichiometry and Algebra. This work shows that it is possible to use data to create ITS capabilities, primarily hint generation, automatically in ways that can help students solve more and more difficult problems, and builds a foundation for effective visualization and exploration of student work for both teachers and researchers

Rationality in discovery : a study of logic, cognition, computation and neuropharmacology

Part I Introduction The specific problem adressed in this thesis is: what is the rational use of theory and experiment in the process of scientific discovery, in theory and in the practice of drug research for Parkinson’s disease? The thesis aims to answer the following specific questions: what is: 1) the structure of a theory?; 2) the process of scientific reasoning?; 3) the route between theory and experiment? In the first part I further discuss issues about rationality in science as introduction to part II, and I present an overview of my case-study of neuropharmacology, for which I interviewed researchers from the Groningen Pharmacy Department, as an introduction to part III. Part II Discovery In this part I discuss three theoretical models of scientific discovery according to studies in the fields of Logic, Cognition, and Computation. In those fields the structure of a theory is respectively explicated as: a set of sentences; a set of associated memory chunks; and as a computer program that can generate the observed data. Rationality in discovery is characterized by: finding axioms that imply observation sentences; heuristic search for a hypothesis, as part of problem solving, by applying memory chunks and production rules that represent skill; and finding the shortest program that generates the data, respectively. I further argue that reasoning in discovery includes logical fallacies, which are neccesary to introduce new hypotheses. I also argue that, while human subjects often make errors in hypothesis evaluation tasks from a logical perspective, these evaluations are rational given a probabilistic interpretation. Part III Neuropharmacology In this last part I discusses my case-study and a model of discovery in a practice of drug research for Parkinson’s disease. I discuss the dopamine theory of Parkinson’s disease and model its structure as a qualitative differential equation. Then I discuss the use and reasons for particular experiments to both test a drug and explore the function of the brain. I describe different kinds of problems in drug research leading to a discovery. Based on that description I distinguish three kinds of reasoning tasks in discovery, inference to: the best explanation, the best prediction and the best intervention. I further demonstrate how a part of reasoning in neuropharmacology can be computationally modeled as qualitative reasoning, and aided by a computer supported discovery system

ISIPTA'07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications

B

Logic-based Technologies for Intelligent Systems: State of the Art and Perspectives

Together with the disruptive development of modern sub-symbolic approaches to artificial intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more and more researchers exploit their potential to make AI more comprehensible, explainable, and therefore trustworthy. Since logic-based approaches lay at the core of symbolic AI, summarizing their state of the art is of paramount importance now more than ever, in order to identify trends, benefits, key features, gaps, and limitations of the techniques proposed so far, as well as to identify promising research perspectives. Along this line, this paper provides an overview of logic-based approaches and technologies by sketching their evolution and pointing out their main application areas. Future perspectives for exploitation of logic-based technologies are discussed as well, in order to identify those research fields that deserve more attention, considering the areas that already exploit logic-based approaches as well as those that are more likely to adopt logic-based approaches in the future

Large-scale migration to an open source office suite: An innovation adoption study in Finland

Avoimeen lähdekoodiin perustuvat ohjelmistot ovat nousseet kaupallisten ohjelmistojen rinnalle sekä liiketaloudellisesti että teknisesti merkittävinä ratkaisuina. Avoimen lähdekoodin ominaisuuksiin sisältyvät mm. ohjelmiston veloitukseton saatavuus ja laajat käyttöoikeudet sekä oikeus ohjelmiston kehittämiseen ja edelleen jakeluun. Organisaatioiden tietohallinnolle ominaisuudet avaavat mahdollisuuksia kustannussäästöihin, yhteisölliseen kehittämiseen sekä toiminta- ja kilpailuttamismahdollisuuksien lisäämiseen. Tunnettuja avoimen lähdekoodin ohjelmistoja ovat esimerkiksi Linux-käyttöjärjestelmä, Firefox-selain sekä OpenOffice.org -toimisto-ohjelmisto. Väitöskirjatutkimus kohdistuu Suomen suurimpaan avoimen lähdekoodin toimisto-ohjelmiston ja asiakirjojen avoimen tallennusmuotostandardin käyttöönottoon. Tutkimuksen kohteena oleva OpenOffice.org -ohjelmiston käyttöönotto käsittää yli 10 000 työaseman tietoteknisen ympäristön oikeusministeriössä ja sen hallinnonalalla. Seitsemän vuoden ajanjakson 2003-2010 kattavassa pitkittäistutkimuksessa sovelletaan suunnittelututkimuksen ja innovaatiotutkimuksen perusteita. Tutkimuksella on sekä teoriaa että käytäntöä palvelevia tuloksia. Tutkimuksen perusteella on perusteltua esittää muutoksia tutkimuksessa testattuun innovaatioiden käyttöönoton yleiseen prosessimalliin. Avoin lähdekoodi alhaisine lisenssikustannuksineen vaikuttaa prosessimalliin tutkimuksen mukaan niin, että vaiheiden ennalta määrätty järjestys ja vaiheiden selkeä erottelu ei ole aina perusteltua. Tutkimus on tuottanut avoimeen lähdekoodiin pohjautuvien innovaatioiden käyttöönottoon tarkoitetun täydennetyn prosessimallin ja siihen liittyvän dokumentointi- ja analysointikehyksen. Tutkimus vahvistaa useita aikaisempia tutkimustuloksia, jotka korostavat mm. organisaation johdon tukea, avoimen lähdekoodin omaksumiskyvyn kasvattamista ja organisaation sisäisen muutosagentin merkitystä avoimen lähdekoodin käyttöönotossa. Käytännön tuloksena tutkimus osoittaa, että avoimen lähdekoodin toimisto-ohjelmistoon siirtyminen on toteutettavissa myös suuressa organisaatiossa ja että siirtymisellä on saavutettavissa merkittäviä etuja. Kustannusten pienentäminen on organisaatioiden useimmin esittämä etu avoimen lähdekoodin käyttöönotosta. Strategisina etuina tuodaan usein esille tietohallinnon itsenäisen aseman vahvistuminen ja toimittajariippuvuuden vähentyminen avoimen lähdekoodin ratkaisuilla ja avoimilla standardeilla. Tutkimuksessa käsitellään useita avoimen lähdekoodin käyttöönotossa tärkeitä näkökohtia, kuten ohjelmiston toiminnallisuutta ja yhteentoimivuutta, kustannusvaikutuksia, ohjelmiston asennusta ja konfigurointia, monikielisyyden tukea, käyttöönottoa tukevia lisäosia, käyttäjäkoulutusta ja -tukea, teknistä tukea ja ohjelmiston käytön seurantaa. Tutkimuksen tulosten mukaan kohdeorganisaatio saavuttaa merkittäviä kustannussäästöjä avoimen lähdekoodin toimisto-ohjelmistoon siirtymisellä verrattuna kaupallisen toimisto-ohjelmiston käyttöön. Tutkimuksessa sovelletut käytännön menetelmät ja monipuolinen toteutuksen ja sen hallinnan kuvaus ovat avuksi organisaatioille niiden harkitessa avoimen lähdekoodin toimisto-ohjelmistoon siirtymistä.This study investigates the largest transition in Finland to an open source office suite and to an open standard for office documents. The IT environment of the open source OpenOffice.org migration involves more than 10 000 workstations in the Finnish Ministry of Justice and its administrative sector. Methodologically, the research is a longitudinal innovation adoption study covering the 7-year time span from 2003 to 2010. The study applies and tests the organizational innovation adoption process model originally developed by Everett Rogers. In addition to the theory-testing approach, the study includes artifact-building and artifact-evaluation activities of design research. The research view of the study introduces a participatory researcher's implementation perspective where the researcher as a staff member of the organization has been in charge of the adoption of the innovation in the organization. The findings of the study provide contributions both to IS research and practice. The events of the study give reason to suggest that the characteristics of the open source software with low-cost licenses call for improvements in the organizational innovation adoption stage model. The findings suggest that the predefined order of stages in the innovation process and sharp distinctions between stages should not be expected in organizational innovation adoption. As a new model and method, the study provides a complementary framework for the instrumentation and documentation of the open source innovation process in the organizational context. The study confirms several results from previous research and practice, especially the importance of top management support, systematic open source skill building and the presence of innovation champions in the adoption of open source solutions. For IS practice, the study shows that the transition to an open source office suite is feasible in a large-scale context and that substantial benefits can be achieved as the result of the transition. For the user organizations of open source software, lower cost has been the most commonly cited benefit and one of the main reasons for adopting open source. Other often cited considerations include strategic goals like the facilitation of more sovereign IT governance and the reduction of vendor dependence through open source solutions and open standards. The study addresses several practically important issues involved in the adoption of open source, e.g., the analysis of software functionality and interoperability, cost evaluations, installation and configuration issues, local language support issues, additional tools to support the migration, user training and support, technical support, and software usage measurements. The evaluation of costs in the study indicates that the migration to the open source office suite platform will benefit the target organization of the study with impressive cost savings when compared to the deployment of a comparative proprietary office suite platform. The study applies numerous best practice approaches which together with the rich insight provided by the research should benefit other organizations considering open source office suite adoptions both from the perspectives of management and implementation