Project acronym LUCRETIUS
Project Foundations for Software Evolution
Researcher (PI) John Mylopoulos
Host Institution (HI) UNIVERSITA DEGLI STUDI DI TRENTO
Call Details Advanced Grant (AdG), PE6, ERC-2010-AdG_20100224
Summary Software evolution refers to changes made to a software system after its deployment. These changes may be caused by changing requirements, domain assumptions, or computing infrastructure, and may affect the system’s implementation, architecture and/or requirements. Evolution may be automatic (aka self-adaptation), or manual, or something in-between. This project aims to develop principles that underlie, and concepts, tools and techniques that support evolution. The project will focus on software-intensive systems. Such systems consist of software, human and organizational elements that work together to fulfill organizational and human objectives. Our proposed research is founded on ideas and research results from Requirements Engineering (RE). Evolution is to be supported by design-time models that are made available at run-time. These models capture system requirements and domain assumptions, augmented with design and implementation details. When evolution is automatic, supported by monitor-diagnose-compensate-execute feedback loops, these models determine (i) what is to be monitored, (ii) whether the system is operating according to its intended purpose, (iii) what are possible compensations for deviations from intended behaviour, (iv) how to evolve the system. When evolution is manual, these models support evolution activities, carried out by humans, by offering a comprehensive picture of the requirements and assumptions under which the system operates, along with traceability links between elements of these models and code. This means that design-time models need to capture stakeholder intentions and commitments, social interactions, business processes, and organizational goals that ultimately determine system requirements. Expected results from the project include the development of novel concepts, tools and techniques for designing evolution-enabled software-intensive systems.
Summary
Software evolution refers to changes made to a software system after its deployment. These changes may be caused by changing requirements, domain assumptions, or computing infrastructure, and may affect the system’s implementation, architecture and/or requirements. Evolution may be automatic (aka self-adaptation), or manual, or something in-between. This project aims to develop principles that underlie, and concepts, tools and techniques that support evolution. The project will focus on software-intensive systems. Such systems consist of software, human and organizational elements that work together to fulfill organizational and human objectives. Our proposed research is founded on ideas and research results from Requirements Engineering (RE). Evolution is to be supported by design-time models that are made available at run-time. These models capture system requirements and domain assumptions, augmented with design and implementation details. When evolution is automatic, supported by monitor-diagnose-compensate-execute feedback loops, these models determine (i) what is to be monitored, (ii) whether the system is operating according to its intended purpose, (iii) what are possible compensations for deviations from intended behaviour, (iv) how to evolve the system. When evolution is manual, these models support evolution activities, carried out by humans, by offering a comprehensive picture of the requirements and assumptions under which the system operates, along with traceability links between elements of these models and code. This means that design-time models need to capture stakeholder intentions and commitments, social interactions, business processes, and organizational goals that ultimately determine system requirements. Expected results from the project include the development of novel concepts, tools and techniques for designing evolution-enabled software-intensive systems.
Max ERC Funding
2 462 095 €
Duration
Start date: 2011-04-01, End date: 2016-03-31
Project acronym MULTIJEDI
Project Multilingual Joint Word Sense Disambiguation
Researcher (PI) Roberto Navigli
Host Institution (HI) UNIVERSITA DEGLI STUDI DI ROMA LA SAPIENZA
Call Details Starting Grant (StG), PE6, ERC-2010-StG_20091028
Summary In the information society the language barrier represents one of the main obstacles to the automatic use, integration and manipulation of knowledge, and this is manifested in the lack of intelligent systems able to perform unified semantic processing of textual resources in a multitude of different languages. To create such systems, a necessary step is to assign the appropriate meanings to the words in documents, a task referred to as Word Sense Disambiguation (WSD). But while WSD is typically performed in a monolingual setting, in order to enable multilingual processing, the semantic connections between word senses (i.e. meanings) in different languages need to be exploited. However, current state-of-the-art systems mainly rely on the existence of bilingual aligned text collections or limited-coverage multilingual resources to perform cross-lingual disambiguation, an unrealistic requirement when working with an arbitrary number of language pairs.
Here we propose a research program that will investigate radically new directions for performing multilingual WSD. The key intuition underlying our proposal is that WSD can be performed globally to exploit at the same time knowledge available in many languages. The first stage will involve the development of a methodology for automatically creating a large-scale, multilingual knowledge base. In a second stage, using this lexical resource, novel graph-based algorithms for jointly performing disambiguation across different languages will be designed and experimented. Crucially, we aim to show that these two tasks are mutually beneficial for going beyond current state-of-the-art WSD systems. The proposed project will have an impact not only on WSD research, but also on related areas such as Information Retrieval and Machine Translation.
Summary
In the information society the language barrier represents one of the main obstacles to the automatic use, integration and manipulation of knowledge, and this is manifested in the lack of intelligent systems able to perform unified semantic processing of textual resources in a multitude of different languages. To create such systems, a necessary step is to assign the appropriate meanings to the words in documents, a task referred to as Word Sense Disambiguation (WSD). But while WSD is typically performed in a monolingual setting, in order to enable multilingual processing, the semantic connections between word senses (i.e. meanings) in different languages need to be exploited. However, current state-of-the-art systems mainly rely on the existence of bilingual aligned text collections or limited-coverage multilingual resources to perform cross-lingual disambiguation, an unrealistic requirement when working with an arbitrary number of language pairs.
Here we propose a research program that will investigate radically new directions for performing multilingual WSD. The key intuition underlying our proposal is that WSD can be performed globally to exploit at the same time knowledge available in many languages. The first stage will involve the development of a methodology for automatically creating a large-scale, multilingual knowledge base. In a second stage, using this lexical resource, novel graph-based algorithms for jointly performing disambiguation across different languages will be designed and experimented. Crucially, we aim to show that these two tasks are mutually beneficial for going beyond current state-of-the-art WSD systems. The proposed project will have an impact not only on WSD research, but also on related areas such as Information Retrieval and Machine Translation.
Max ERC Funding
1 288 400 €
Duration
Start date: 2011-02-01, End date: 2016-01-31
Project acronym NEUROINT
Project How the brain codes the past to predict the future
Researcher (PI) Uri Hasson
Host Institution (HI) UNIVERSITA DEGLI STUDI DI TRENTO
Call Details Starting Grant (StG), SH4, ERC-2010-StG_20091209
Summary The overarching objective of this research program is to use neuroimaging methods to determine how the recent past is coded in the human brain and how this coding contributes to the processing of incoming information. A central tenet of this proposal is that being able to maintain a representation of the recent past is fundamental for constructing internal predictions about future states of the environment. The construction of such has been called predictive coding, such predictions have been argued to play a fundamental role in disambiguating signal information from a noisy or degraded array.
We implement a comprehensive and multi-disciplinary research program to understand how regularities in the recent past are coded, and how they give rise to predictive codes of future states. On the basis of prior work we propose that disambiguation of signals is performed by a predictive system that relies strongly on representing the statistical properties of the recent past. This system is instantiated via interactions between three neural systems: (1) medial temporal structures including the hippocampus and parahippocampal cortex that encode statistical features of the recent past and signal whether predictions are licensed, (2) higher level cortical regions that code for detailed predictions in various modalities and generate efferent top-down predictions, and (3) lower-level sensory cortices whose activity at any given moment reflects not only bottom-up processing of sensory inputs, but also the assessment of these inputs against top-down predictions propagated from higher-levels regions. We will use neuroimaging methods with high spatial and temporal resolution (fMRI, MEG) to study neural activity in these three neural systems and the interaction between them.
Summary
The overarching objective of this research program is to use neuroimaging methods to determine how the recent past is coded in the human brain and how this coding contributes to the processing of incoming information. A central tenet of this proposal is that being able to maintain a representation of the recent past is fundamental for constructing internal predictions about future states of the environment. The construction of such has been called predictive coding, such predictions have been argued to play a fundamental role in disambiguating signal information from a noisy or degraded array.
We implement a comprehensive and multi-disciplinary research program to understand how regularities in the recent past are coded, and how they give rise to predictive codes of future states. On the basis of prior work we propose that disambiguation of signals is performed by a predictive system that relies strongly on representing the statistical properties of the recent past. This system is instantiated via interactions between three neural systems: (1) medial temporal structures including the hippocampus and parahippocampal cortex that encode statistical features of the recent past and signal whether predictions are licensed, (2) higher level cortical regions that code for detailed predictions in various modalities and generate efferent top-down predictions, and (3) lower-level sensory cortices whose activity at any given moment reflects not only bottom-up processing of sensory inputs, but also the assessment of these inputs against top-down predictions propagated from higher-levels regions. We will use neuroimaging methods with high spatial and temporal resolution (fMRI, MEG) to study neural activity in these three neural systems and the interaction between them.
Max ERC Funding
978 678 €
Duration
Start date: 2011-01-01, End date: 2015-12-31
Project acronym PASCAL
Project Processing Activates Specific Constraints for Language Acquisition
Researcher (PI) Jacques Mehler
Host Institution (HI) SCUOLA INTERNAZIONALE SUPERIORE DI STUDI AVANZATI DI TRIESTE
Call Details Advanced Grant (AdG), SH4, ERC-2010-AdG_20100407
Summary PASCAL is a project to investigate the human ability to acquire language, and the underlying biological endowment that provides specific language learning mechanisms. Clearly, language acquisition (LA) starts at birth, rendering neonates the first population to investigate, to get the full picture of how LA unfolds. PASCAL’s first objective is thus to investigate core cognitive dispositions, which render neonates able to interact with speech signals. We will focus on the neonates’ and young infants’ abilities to process auditory signals and to store them in memory. The second objective is to identify biological constraints that determine LA dispositions, in particular we will study the speech perception preferences in infants who do not yet produce speech, to understand if practice with the articulators is necessary to determine such preferences. The third objective, linked to the former one, is to understand the beginning of prosodic grouping abilities that might trigger the initialization of grammar. The fourth objective is to identify the origin of the functional specialization of segmental categories in speech processing. How early in life do consonants become specialized for lexical processing, and vowels for the extraction of regularities? The fifth objective is to explore a basic issue in LA, namely the type of bilingual exposure at different ages and their consequences for the enhancement of executive functions. We will also develop games to promote executive functions to complement the full immersion into a new language that children may get at different points in time. The results of this part of our project might have an important impact on educational policies.
Summary
PASCAL is a project to investigate the human ability to acquire language, and the underlying biological endowment that provides specific language learning mechanisms. Clearly, language acquisition (LA) starts at birth, rendering neonates the first population to investigate, to get the full picture of how LA unfolds. PASCAL’s first objective is thus to investigate core cognitive dispositions, which render neonates able to interact with speech signals. We will focus on the neonates’ and young infants’ abilities to process auditory signals and to store them in memory. The second objective is to identify biological constraints that determine LA dispositions, in particular we will study the speech perception preferences in infants who do not yet produce speech, to understand if practice with the articulators is necessary to determine such preferences. The third objective, linked to the former one, is to understand the beginning of prosodic grouping abilities that might trigger the initialization of grammar. The fourth objective is to identify the origin of the functional specialization of segmental categories in speech processing. How early in life do consonants become specialized for lexical processing, and vowels for the extraction of regularities? The fifth objective is to explore a basic issue in LA, namely the type of bilingual exposure at different ages and their consequences for the enhancement of executive functions. We will also develop games to promote executive functions to complement the full immersion into a new language that children may get at different points in time. The results of this part of our project might have an important impact on educational policies.
Max ERC Funding
2 500 000 €
Duration
Start date: 2011-07-01, End date: 2016-06-30
