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 action’s 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.
Fields of science
- natural sciencesbiological sciencesneurobiology
- natural sciencescomputer and information sciencesartificial intelligence
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationsradio technologyradio frequency
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- natural sciencesmathematicsapplied mathematicsstatistics and probability
Keywords
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Topic(s)
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
00185 Roma
Italy