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Help Me Grow: Artificial Cognitive Development via Human-Agent Interactions Supported by New Interactive, Intrinsically Motivated Program Synthesis Methods.

Project description

A new way to think about artificial cognitive systems

Artificial intelligence (AI) is the future. Machines that can interact with the world and learn skills is an ambitious goal in AI. However, this future hinges on how well we build autonomous agents and whether we can program them to solve problems. In this context, the Marie Skłodowska-Curie Actions INTERACT project will explore artificial cognitive systems to understand the limits of current AI systems. Specifically, it will build on the following three methods: Bayesian program induction, intrinsically motivated learning, and human-machine linguistic interactions. The aim is to open research avenues for more interpretable, performant and adaptive AI systems. This will result in scientific (interactive program synthesis approaches), societal (democratised AI training) and economic impacts (adaptive AI assistants).

Objective

Building machines that interact with their world, discover interesting interactions and learn open-ended repertoires of skills is a long-standing goal in AI. This project aims at tackling the limits of current AI systems by building on three families of methods: Bayesian program induction, intrinsically motivated learning and human-machine linguistic interactions. It targets three objectives: 1) building autonomous agents that learn to generate programs to solve problems with occasional human guidance; 2) studying linguistic interactions between humans and machines via web-based experiments (e.g. properties of human guidance, its impact on learning, human subjective evaluations); and 3) scaling the approach to the generation of constructions in Minecraft, guided by real players. The researcher will collaborate with scientific pioneers and experts in the key fields and methods supporting the project. This includes supervisors Joshua Tenenbaum (program synthesis, MIT) and Pierre-Yves Oudeyer (autonomous learning, Inria); diverse collaborators, and an advisory board composed of an entrepreneur and leading scientists in developmental psychology and human-robot interactions. The 3rd objective will be pursued via a secondment with Thomas Wolf (CSO) at HuggingFace, a world-leading company in the open source development of natural language processing methods and their transfer to the industry. By enabling users to participate in the training of artificial agents, the project aims to open research avenues for more interpretable, performant and adaptive AI systems. This will result in scientific (e.g. interactive program synthesis approaches), societal (e.g. democratized AI training) and economic impacts (e.g. adaptive AI assistants). The dissemination, communication and exploitation plans support these objectives by targeting scientific (AI, cognitive science), industrial (video games, smart homes) and larger communities (gamers, software engineers, large public).

Fields of science (EuroSciVoc)

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-TMA-MSCA-PF-GF - HORIZON TMA MSCA Postdoctoral Fellowships - Global Fellowships

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Call for proposal

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(opens in new window) HORIZON-MSCA-2021-PF-01

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Coordinator

INSTITUT NATIONAL DE RECHERCHE EN INFORMATIQUE ET AUTOMATIQUE
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.

€ 276 681,60
Address
DOMAINE DE VOLUCEAU ROCQUENCOURT
78153 Le Chesnay Cedex
France

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