Objective
"While language is a natural way to interact with artificial characters
or agents in video games, communication with agents currently tends to
be limited to menu systems. To achieve smooth linguistic
communication, utterances need to be grounded in the situation in
which they occur. That is, the meanings of utterances must be learned
from observing their use in some naturally occurring perceptual
context. Recent years have seen much progress in the development of
visually- or auditorily-grounded language understanding using novel
machine learning techniques such as deep learning. At the same time,
companies like Google DeepMind have introduced deep learning models
that can learn to play games at super-human levels. We propose to take
this research to the next step, by grounding natural language in video
games.
Grounding natural language in video games yields two main
benefits. The first benefit is commercial in nature: with the global
market for video games expected to reach $100 billion by 2017, there
is clearly a large demand for more sophisticated interaction with
in-game agents. Secondly, video games are a natural way to explore
artificial intelligence techniques in a ""simulated"" world that is
easier to understand computationally than the extremely complicated
""real"" world.
The current project will explore natural language grounding in a small
number of appropriate games. Once we are capable of grounding natural
language in these games, we can translate utterances into
straightforward actions for artificial agents. An example might be
telling your team members to follow you, to take the left flank, or to
duck when they are being shot at. Given the recent developments in
machine learning and grounded language understanding, we believe that
now is the perfect moment to explore these possibilities further.
"
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.
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.
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
- natural sciences computer and information sciences software software applications video games
You need to log in or register to use this function
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
See all projects funded under this programme
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.
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.
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.
ERC-POC - Proof of Concept Grant
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2015-PoC
See all projects funded under this callHost institution
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.
CB2 1TN CAMBRIDGE
United Kingdom
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.