MAGMA - Socially Relevant Multi-Agent systems
Ancienne Joint research team between CNRS, Grenoble INP, UGA
+33 4 76 51 46 24
The term Multi-agent system was originally coined to mean a collection of software agents interacting within a computer environment. From this beginning, the community’s view of MAS was extended to include other types of entities such as virtual characters, robots, and humans, all interacting in a broader interpretation of a system. We have now arrived at a situation where our extended view of a social-technical system is composed of a multitude of different types of agents, interacting in mutually beneficial ways. In this new social system, the term utility takes on new meaning, referring to something that is of value for the mixed agent community as a whole, or a sub-set of it.
In this light, MAGMA focuses on the study, development and use of autonomous agents (AA) and MAS to solve problems that address a social concern or issue. Its goal is to produce AA and MAS that are of value to citizens, solving real-world problems and enriching society. Concentrating on AA and MAS that have an individual and social utility, we are interested in developing new roles for AA and MAS in society. In order to study and develop socially relevant AA and MAS, we must address a number of scientific challenges:
  • Analysis, modelling, and replication of human reasoning, social behaviours and emotional factors,
  • Representation and formalisation of artificial agents,
  • Personalisation of artificial agents and agent groups,
  • Representing long term relationships between human and artificial companions (social robots or virtual characters),
  • Creation and validation of well-grounded agent-based models,
  • Understanding society as a complex system, including the emergence of collective phenomena and collective intelligence, and the design of robust and resilient socio-technical systems,
  • Developing adaptive/human-aware planning algorithms,
  • Engineering large scale and scalable MAS,
  • Ensuring agents’ privacy and data confidentiality,
  • Micro and macroscopic observation of natural and artificial systems,
  • Analysis and prediction of system dynamics and social networks.
The social challenges of our team include:
  • Ensuring acceptability and/or believability of AA and MAS
  • Engendering Social intelligence (self and social awareness, including sincerity, empathy, politeness, etc.)
  • Promoting natural/easy interaction with humans
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