Abduction, Reason and Science

Magnani, Lorenzo

doi:10.1007/978-1-4419-8562-0

Cited by 407 publications

(45 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In the nineteenth century, Charles Sanders Peirce (Harstshorne, 1958;Peirce, 1957) sets out clearly these three forms of syllogistic reasoning-deduction, abduction and induction-and studies their respective role in the development of scientific theories. More recently, several authors (see for example the books (Holland, 1989;Josephson and Josephson, 1994;Magnani, 2001;) have studied abduction and induction from the perspective of Artificial Intelligence and Cognitive Science. In particular, the work in is devoted to the problem of comparing these two forms of reasoning and investigating their possible unification or integration for the purposes of Artificial Intelligence.…”

Section: Logical Modelling Of Scientific Theoriesmentioning

confidence: 99%

Application of abductive ILP to learning metabolic network inhibition from temporal data

et al. 2006

View full text Add to dashboard Cite

In this paper we use a logic-based representation and a combination of Abduction and Induction to model inhibition in metabolic networks. In general, the integration of abduction and induction is required when the following two conditions hold. Firstly, the given background knowledge is incomplete. Secondly, the problem must require the learning of general rules in the circumstance in which the hypothesis language is disjoint from the observation language. Both these conditions hold in the application considered in this paper. Inhibition is very important from the therapeutic point of view since many substances designed to be used as drugs can have an inhibitory effect on other enzymes. Any system able to predict the inhibitory effect of substances on the metabolic network would therefore be very useful in assessing the potential harmful side-effects of drugs. In modelling the phenomenon of inhibition in metabolic networks, background knowledge is used which describes the network topology and functional classes of inhibitors and enzymes. This background knowledge, which represents the present state of understanding, is incomplete. In order to overcome this incompleteness hypotheses are considered which consist of a mixture of specific inhibitions of enzymes (ground facts) together with general (non-ground) rules which predict classes of enzymes likely to be inhibited by the toxin. The foreground examples are derived from in vivo experiments involving NMR analysis of time-varying metabolite concentrations in Mach Learn (2006) 64:209-230 rat urine following injections of toxins. The model's performance is evaluated on training and test sets randomly generated from a real metabolic network. It is shown that even in the case where the hypotheses are restricted to be ground, the predictive accuracy increases with the number of training examples and in all cases exceeds the default (majority class). Experimental results also suggest that when sufficient training data is provided, non-ground hypotheses show a better predictive accuracy than ground hypotheses. The model is also evaluated in terms of the biological insight that it provides.

show abstract

Section: Logical Modelling Of Scientific Theoriesmentioning

confidence: 99%

Application of abductive ILP to learning metabolic network inhibition from temporal data

et al. 2006

View full text Add to dashboard Cite

show abstract

“…Deduction alone cannot deal with the irrational sets needed to capture the phenomenology of a changing world and of human responses to it. We have not strictly used the abductive cycle as an hypothesis generator (Gooding 1996;Hanson 1958;Magnani 1998Magnani , 2001. Rather, we have emulated abduction through look-up tables representing the experimental phenomenology for each hypothesis.…”

Section: Discussionmentioning

confidence: 99%

Simulation Methods for an Abductive System in Science

Addis

Gooding

2007

Found Sci

View full text Add to dashboard Cite

We argue that abduction does not work in isolation from other inference mechanisms and illustrate this through an inference scheme designed to evaluate multiple hypotheses. We use game theory to relate the abductive system to actions that produce new information. To enable evaluation of the implications of this approach we have implemented the procedures used to calculate the impact of new information in a computer model. Experiments with this model display a number of features of collective belief-revision leading to consensus-formation, such as the influence of bias and prejudice. The scheme of inferential calculations invokes a Peircian concept of 'belief' as the propensity to choose a particular course of action.

show abstract

“…A continuación presentamos cuatro ejemplos de respuestas erróneas de estudiantes que nos permitirán interpretar -por inducción cualitativa (LIPTON, 1991;MAGNANI, 2001) -posibles orígenes de dificultades para aprender química a partir de su complejo discurso. …”

Section: Los Estudiantes Saben "Algo" Pero Cometen Errores…unclassified

Algunas reflexiones sobre la distancia entre "hablar química" y "comprender química"

Galagovsky

Bekerman

Giacomo

et al. 2014

Ciênc. educ. (Bauru)

View full text Add to dashboard Cite

Resumen: Una clase de química puede ser considerada como un espacio de comunicación entre el docente experto y los estudiantes novatos, donde los lenguajes utilizados son la interfase explícita y observable del intercambio comunicativo. En el presente trabajo se muestra con dos ejemplos cómo la diversidad de lenguajes químicos en lugar de favorecer la comprensión de los estudiantes, puede actuar como fuente de obstáculos que dificultan la comunicación en el aula. Así mismo, se analizará con otros dos ejemplos cómo el discurso con el que se enseña la disciplina también es potencial generador de errores en los estudiantes, cuando ellos construyen sus modelos mentales idiosincrásicos a partir de un discurso recortado y simplificado, desde las mejores intenciones de realizar buenas transposiciones didácticas. Se plantea que un enfoque de análisis de la situación de aula como un encuentro comunicativo entre experto y novato conduce a una necesaria diferenciación entre "hablar química" y "comprender química".Palabras clave: Enseñanza de química. Comunicación. Discurso. Didáctica. Aprendizaje. Abstract:A class of chemistry can be considered as a forum for communication between the expert teacher and novice students, where the languages used are explicit and observable interface of a communicative exchange. In this paper we show, with two examples, how the diversity of chemical languages, instead of promoting student understanding, it can act as a source of barriers to communication in the classroom. Also, will be discussed in two examples how the speech with which the discipline is taught is also generating potential errors in students when they build their idiosyncratic mental models from a cut and simplified speech from the best intentions of make good didactic transpositions. It is argued that an approach to analysis of the situation in the classroom as a communicative encounter between expert and novice leads to a necessary distinction between "talking chemistry" and "understanding chemistry."

show abstract

Abduction, Reason and Science

Cited by 407 publications

References 0 publications

Application of abductive ILP to learning metabolic network inhibition from temporal data

Application of abductive ILP to learning metabolic network inhibition from temporal data

Simulation Methods for an Abductive System in Science

Algunas reflexiones sobre la distancia entre "hablar química" y "comprender química"

Contact Info

Product

Resources

About