SEMESTER 1 (30 ECTS)

The course will focus on the concept of “scientific explanation,” conceived as a cross-sectional approach that allows us to examine the major problems specific to the philosophy of science.

The course comprises three parts:
1) What does it mean to explain?
2) What is the object of scientific explanation?
3) What type of discourse is scientific explanation?

Physical sciences and biology will serve as the primary sources of examples.

In the first part, comprising the initial 6 sessions, we will analyze what constitutes an explanation and the need it addresses. This will provide an opportunity to present and discuss the principal models of scientific explanation, particularly in contemporary philosophical literature, concluding with the experimental method and statistical testing.

The second part, spanning approximately 3 sessions, will emphasize that what requires explanation is not a pre-given invariant but depends, in each case, on a particular scientific representation of reality, as well as on the technical means that enable us to identify the facts requiring explanation.

Nevertheless, the uniformity of nature remains a regulative ideal of scientific rationality, to be distinguished from both determinism and reductionism. It is with this observation that the third part will begin, covering the final 3 sessions. This third and concluding part will focus on the uniformity of scientific theories—that is, on the forms common to these discourses that constitute different scientific theories. We will address, in particular, the concepts of law and convention, the role of mathematical formalism, and the question of the unity of sciences.

Philosophy of science encompasses not only vastly different domains (linked to different sciences) but also diverse philosophical perspectives: perspectives that accord varying degrees of importance to the history of science, or that emphasize to different extents the specificities of various sciences.

The theme of scientific explanation will constitute, as stated, a means of traversing this multiform domain while being sufficiently general to encompass its principal aspects. The approach will indeed account for sciences in their historicity and variety, but the underlying premise is that it remains possible to describe the methodology common to all sciences through general concepts. In other words, the premise is that philosophy of science can remain an epistemology, anchored at the heart of theoretical philosophy.

Bibliography:
• A. Barberousse, D. Bonnay & M. Cozic, Précis de philosophie des sciences, Vuibert, 2011.
• R. Carnap, Les fondements philosophiques de la physique, Armand Colin, 1973.
• A. F. Chalmers, Qu’est-ce que la science ?, Le Livre de Poche, 1990.
• J.-R. Vernes, Critique de la raison aléatoire, Aubier, 1982.

Assessment Methods:
One take-home assignment during the semester on a general topic related to the course.

This course consists of two parts: Syntax (3 ECTS) and Semantics (3 ECTS).

Syntax: The objective of this course is to introduce students to the issues, methods, and questions of theoretical syntax. The approach focuses on contemporary syntax models through a comparison of Chomskian models (Principles and Parameters, Minimalist Program) and their alternatives (GPSG; HPSG) across domains such as sentence structure, grammatical functions, and non-local dependencies. The course is structured over twelve sessions interspersed with tutorials.

Semantics: This course continues the study of the empirical domain of contemporary formal semantics. One of its objectives is to facilitate mastery of different concepts and formalization procedures concerning a theory of meaning, enabling the analysis of specific problems and, more generally, the practice of research. The course will cover various questions, including the extension of ontology (and semantic types) required for domains such as event processing.

LCHAY010 : Language and its interfaces (M1S1)

(Course in English), (2h) 6 ECTS

LCHAY010: Language and Its Interfaces (M1S1)

(Course taught in English) • 2 hours • 6 ECTS

A central question for many natural social systems examined from various perspectives in this course is: How does meaning emerge through interaction within these systems? These perspectives can be explored by asking questions such as: What constitutes meaning in natural language? What is the relationship between natural language meaning and meaning among interaction systems of other species? To what extent is the grammar underlying natural language genetically encoded, and to what extent does it emerge from interaction? How do we apply concepts of meaning to analyze cognitive experience in artistic media such as theater and music?

Topics covered include: communicative interaction among non-human adults, language acquisition and interaction, an interaction-based view of language, the meaning of manual and facial gestures, language and theater, language and humor, the relationship between music and language, and the meaning of poetry.

Coordinator: Jonathan GINZBURG (yonatan.ginzburg@u-paris.fr)

Bibliography:

• Clark, A. & Eyraud, R. (2006). Learning auxiliary fronting with grammatical inference. Proceedings of the Tenth Conference on Computational Natural Language Learning (CoNLL-X), 125–132.
• Elam, K. (2002). The Semiotics of Theatre and Drama. Routledge.
• Ginzburg, J. & Poesio, M. (2016). Grammar is a system that characterizes talk in interaction. Frontiers in Psychology, 7, 1938.
• Griebel, U., Pepperberg, I. M., & Oller, D. K. (2016). Developmental plasticity and language: A comparative perspective. Topics in Cognitive Science, 8(2), 435–445.
• Halliday, M. A. K. (1975). Learning How to Mean: Explorations in the Development of Language. Edward Arnold.
• Patel, A. D. (2010). Music, Language, and the Brain. Oxford University Press.
• Paterson, D. (2018). The Poem: Lyric, Sign, Metre. Faber & Faber.
• Trouvain, J. & Truong, K. P. (2017). Laughter. In The Routledge Handbook of Language and Humor. Routledge.
• Wagner, P., Malisz, Z., & Kopp, S. (2014). Speech and gesture in interaction: An overview. Speech Communication, 57, 209–232.

This course introduces the fundamentals of machine learning applied to Natural Language Processing (NLP). Students will discover the principal techniques and algorithms used to analyze and process natural language using computational methods.

(Course taught in English)