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Multimodal Agents Grounded via Interactive Communication

Objective

One of the main goals of artificial intelligence is to build artificial agents that can interact with humans using natural language. To fully master language, an agent needs to know how to use it to accomplish a goal; to interact with another speaker; and to refer to objects in the external reality. My research project aims at equipping an artificial agent with all these skills in one single learning framework.

Communication helps humans accomplish things in the world and cooperate with each other, resulting in continuous and incremental updating of the speakers’ knowledge state. However, traditional machine learning methods used to model language are based on static and passive regimes, and are typically not grounded in external reality. I propose a radically different research programme, based on recent advancements in training neural networks using reinforcement learning, that will enable the move from a static, fully supervised to a dynamic, interactive learning where the agents need to use language to accomplish a task in the visual world. This will dramatically accelerate the development of machines that can talk with humans.

Even though I am an established researcher in computational linguistics, with substantial contributions to the integration of language and vision, I still need to fully develop my own line of research to become a leading, independent researcher in Europe. Carrying out the present proposal at Universitat Pompeu Fabra and Facebook Artificial Intelligence Research will be a fundamental step towards achieving my goal, since my hosts are leaders in computational linguistics, machine learning, and artificial intelligence in general, and specifically in the methods needed for the present proposal. Conversely, my unique profile, bridging computational linguistics and computer vision with machine learning methods, will widen the scope and outreach of the research conducted at both groups.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.

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Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-MSCA-IF-2017

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Coordinator

UNIVERSIDAD POMPEU FABRA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 158 121,60
Address
PLACA DE LA MERCE, 10-12
08002 Barcelona
Spain

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Region
Este Cataluña Barcelona
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 158 121,60
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