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Contextual Radio Cues for Enhancing Decision Making in Networks of Autonomous Agents

Project description

Environmental radio cues for autonomous agent decision-making

Radio cues, employing radio-frequency sensors, offer electromagnetic information with contextual meaning, empowering agents to predict outcomes and navigate social environments more efficiently. The interpretation of contextual radio cues involves the exchange of information while considering other agents' abilities to process environmental stimuli. The ERC-funded CUE-GO project is pioneering a new framework for autonomous agents to enhance decision-making through the utilisation of environmental radio cues. This encompasses the development of methods for extrapolating radio cues, cue-guided navigation algorithms, and assessments for future predictions. Drawing insights from diverse fields, including behavioural neuroscience and engineering, the project will make strides in human-inspired decision-making for autonomous agents. CUE-GO envisions a society where humans and AI coexist seamlessly.

Objective

The CUE-GO project aims to conceive a novel methodological framework for enhancing the decision-making capabilities of autonomous agents through the exploitation of contextual radio cues of the environment. Radio cues represent a quantum leap from the traditional concept of features, usually retrieved by vision-based systems, as they contain electromagnetic information with semantic meanings (contextual) enabled by radio-frequency sensors, like those at TeraHertz bands. The elaboration of contextual radio cues allows a far-reaching prediction of the outcomes of agents behaviors and ultimately yields a more efficient navigation in social environments, more accurate localization of people and objects, and enhanced cooperation toward a common mission goal. In interpreting contextual radio cues, agents exchange their sensed information in a way that considers other agents expertise, i.e. their abilities to process environmental stimuli.

To achieve this vision, I will: (1) develop a general framework for the decision-making of autonomous agents that emulates the human capability of interpreting cues for anticipating an actions course; (2) conceive and design methods for extrapolating contextual radio cues based on high-resolution semantic mapping of the environment; (3) conceive and design cue-guided localization and navigation algorithms that will boost ambient awareness; (4) conceive new methods and metrics to assess the agents skills in associating contextual radio cues with statistical models that accurately predict future rewards or punishments; (5) develop collaboration schemes accounting for the assessment of agents expertise.

Thanks to a multidisciplinary approach, combining diverse knowledge from behavioral neuroscience to engineering, this project will lead to a significant advance in human-inspired decision-making for future networks of autonomous agents, toward a society where humans and artificial intelligence co-exist in the same environment.

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Call for proposal

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(opens in new window) ERC-2023-STG

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Host institution

ALMA MATER STUDIORUM - UNIVERSITA DI BOLOGNA
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.

€ 1 055 314,00
Address
VIA ZAMBONI 33
40126 Bologna
Italy

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Region
Nord-Est Emilia-Romagna Bologna
Activity type
Higher or Secondary Education Establishments
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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.

€ 1 055 314,00

Beneficiaries (2)

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