Courses' slots:
Week two 17:00 - 18:30
Logic and Computation introductory course:
Explanation in Ontology Languages.
Teachers
- Bijan Parsia ()
- Thomas Schneider ()
Course material: explanation.pdf
Abstract:This course will present current research into explanations, which can answer questions such as: "Why do certain entailments follow from my ontology?"; "Why is my ontology inconsistent?"; "Which part of my ontology do I need to modify in order to prevent an undesired entailment?" These questions are of relevance to ontology developers in various domains including bioinformatics, medicine, geography, linguistics. We will focus on proof based explanation techniques and touch on the emerging field of model based explanation.
Language and Logic advanced course:
Referent Systems.
Teachers
- Udo Klein ()
- Marcus Kracht ()
Formal systems for computing meanings often rely very strongly
on syntactic structure, and rarely on other overt clues such as
morphology. This makes them quite inflexible. The calculus of
Referent Systems, due to Kees Vermeulen and further developed
by the second lecturer, allows for much more flexible
algorithms since it accesses both syntactic and morphological
structure. The basic idea is that semantic composition is not
performed by function application, but by a semantic operation
which merges variables depending on the morphosyntactic
properties associated with them. The main burden for
calculating meanings of complex expressions is carried by the
argument structure, which interfaces syntax, morphology and
semantics. The system has been implemented (see ). The
course will not only introduce the idea of referent systems and
how they function, but also show how to implement and use the
system.
The course assumes knowledge of formal semantics (DRT, for
example) and some general knowledge of linguistics. All formal
concepts will be properly introduced.
Proposed Content:
Lec 1: Motivation and basic idea: Composing meanings
Lec 2: Referent systems
Lec 3: Case
Lec 4: Parameters
Lec 5: Agreement Morphology and its Role in Semantics
Language and Computation introductory course:
Corpus-Based Argument Structure.
Teacher
Abstract: The aim of the course is twofold. The linguistic goal is to discuss the notion of argument structure (valence) both from the syntactic and from the semantic point of view, with some emphasis on the argument/adjunct dichotomy and diathesis (argument alternations). The computational goal is to present diverse techniques of learning valence information from corpora. This automatic learning task is usually split into two stages: the linguistic stage of collecting information about the co-occurrence of argument-taking lexemes and various types of phrases (possible arguments), and the statistical inference stage at which reliable valence hypotheses are selected. Both stages will be discussed in detail. The course will conclude with the presentation of various evaluation methods and various uses of automatically extracted valence information. The closing bracket of the course will be the discussion of the extent to which automatic valence acquisition can help in distinguishing arguments from adjuncts.
Language and Computation advanced course:
Distributional Semantic Models - Theory and Empirical Results.
Teachers
- Stefan Evert ()
- Alessandro Lenci ()
Distributional semantic models (DSMs) are based on the
assumption that the meaning of a word can (at least to a certain
extent) be inferred from its usage, i.e. its distribution in
text. Therefore, these models dynamically build semantic
representations "in the form of multi-dimensional vector
spaces" through a statistical analysis of the contexts in
which words occur.
With their distributed vector-space representations, DSMs
challenge traditional symbolic accounts of conceptual and
semantic structures. However, their true ability to address key
issues of lexical meaning is still poorly understood, and will
have to be carefully evaluated in linguistic and cognitive
research.
This course aims to equip participants with the necessary
background knowledge for carrying out such research. In addition
to the mathematical foundations of DSMs and their application to
semantic analysis, we will put particular emphasis on relating
the computational models to fundamental issues of semantic
theory.
Language and Logic workshop:
Formal approaches to sign languages.
Organizers
- Carlo Cecchetto ()
- Carlo Geraci ()
Course material: 02 Brentari Eccarius ESSLLI 2009.pdf 03 Schlenker ESSLLI 2009.pdf 04 Koulidobrova ESSLLI 2009.pdf 05 Davidson Caponigro Mayberry ESSLLI 2009.pdf 06 Neidle et al ESSLLI 2009.pdf 08 MathurRathmann ESSLLI 2009.pdf 09 Bernaht ESSLLI 2009.pdf 10 Aboh Pfau 2009 ESSLLI.pdf 11 Donati Branchini ESSLLI 2009.pdf
Abstract:The recognition that sign languages are natural languages in their own right, and not collections of gestures or impoverished codes lacking an autonomous grammar, begins with Stokoe (1960). With Stokoe's work, the methods linguists use to describe and investigate spoken languages are applied to sign languages as well. In recent years, linguistic work on sign languages has also developed in formal frameworks, in the areas of phonology, syntax, and semantics. One goal of the workshop is to bring together researchers from different areas of formal linguistics who are investigating sign languages. The grammars of sign languages are as highly complex as the grammars of spoken languages and share with them many universal features, despite the difference in modality between spoken languages (which use the auditory channel) and sign languages (which use the visual channel). Yet, sign languages also differ from spoken languages in radical ways: morphological information in sign languages is often conveyed simultaneously by different articulators rather than linearly; moreover, certain aspects of their phonological, syntactic and semantic structures are not commonly found in spoken languages. These differences raise an interesting challenge for existing formal linguistic frameworks, which are designed to account for the grammars of spoken languages. By bringing together formal linguists working on sign languages, the workshop should contribute to meet this challenge.
Logic and Computation introductory course:
Logics and Agent Programming Languages
Teachers
- Natasha Alechina ()
- Brian Logan ()
Keywords: agent programming languages, logical models of agency, verification
Abstract:
To create a language for programming entities capable of intelligent behaviour (`agents'), researchers and developers must address deep questions such as: what are the basic constituent parts of an intelligent agent; how should the agent `think' (e.g., which deliberation strategy should it employ -- should it plan a precise sequence of actions in advance or should it adopt an abstract plans with gaps `to be filled-in later'); what relationship should there be between the agent's beliefs and its goals, etc. In seeking to address these questions, researchers have drawn heavily on formal models of agents and on agent logics, including epistemic logics, logics of action, dynamic logic, coalition logics etc. For example, the development of agent programming languages such as AgentSpeak were heavily influenced by the BDI (Beliefs, Desires and Intentions) logics developed to understand what an agent's behaviour should be. These interactions have resulted in an extremely fruitful cross fertilisation between work in logic and computation, and the application of logical techniques to address key practical issues such as the verification of agent programs (i.e., will an agent program meet the specification set out by its developers).
This course will address key topics in logics of agent programs including: the Belief Desire Intention model; overview of agent programming languages based on the BDI model; relationship between the operational semantics of BDI-based agent programming languages and logics for reasoning about agents' beliefs and intentions; verification of agent programs using model checking and theorem proving. The course assumes some exposure to modal logic, but no prior knowledge of agent programming languages is required.