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Hypermedia Communities of People and Autonomous Agents
Type
fundamental research project
Start Date
01 October 2019
Acronym
HyperAgents
Status
ongoing
Keywords
Web Architecture
Multiagent Systems
Semantic Web
Distributed Artificial Intelligence
Hypermedia
Industry 4.0
Online Disinformation
Description
The HyperAgents project aims to enable the deployment of world-wide hybrid communities of people and autonomous agents on the Web. For this purpose, HyperAgents defines a new class of multi-agent systems (MAS) that use hypermedia as a general mechanism for uniform interaction such that they are: (i) aligned with the Web architecture to inherit the properties of the Web as a world-wide, open, and long-lived system, and (ii) transparent and accountable to support acceptance by people. We refer to this new envisioned class of Web-based MAS as Hypermedia MAS. The HyperAgents project proposes: (1) to define an architectural style for Hypermedia MAS that induces the above-mentioned properties, (2) to define declarative languages and mechanisms for specifying, enacting, and regulating interactions among people and autonomous agents in Hypermedia MAS, (3) to develop an open-source software infrastructure for Hypermedia MAS that enables the deployment of hybrid communities on the Web, and (4) to demonstrate the deployment of prototypical hybrid communities in two application areas: (i) Industry 4.0 and (ii) tackling online disinformation. To undertake this investigation, the project consortium brings together internationally recognized researchers actively contributing to research on autonomous agents and MAS, the Web architecture, Semantic Web, and to the standardization of the Web. Being able to harness the collective power of Web-scale hybrid communities and to focus it on specific problems would have extensive implications in a broad range of domains: for manufacturers, it could enable distributed intelligent manufacturing at global scale; for citizens, it could enable access to transparent and trustworthy online information. We expect that the work conducted in this project will break new ground in AI and Web research and that its applications will cut across society.
Leader contributor(s)
Partner(s)
Prof. Dr. Olivier Boissier
Prof. Dr. Fabien Gandon
Funder(s)
Range
HSG + other universities
Range (De)
HSG + andere
Division(s)
Eprints ID
247871
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PublicationSignifiers as a First-class Abstraction in Hypermedia Multi-Agent Systems(International Foundation for Autonomous Agents and Multiagent Systems, 2023-05-30)Hypermedia APIs enable the design of reusable hypermedia clients that discover and exploit affordances on the Web. However, the reusability of such clients remains limited since they cannot plan and reason about their interactions. This paper provides a conceptual bridge between hypermedia-driven affordance exploitation on the Web and methods for representing and reasoning about actions that have been extensively explored in Multi-Agent Systems (MAS) and, more broadly, Artificial Intelligence. We build on concepts and methods from Affordance Theory and Human-Computer Interaction to introduce signifiers as a first-class abstraction in Web-based MAS: Signifiers are designed with respect to the agent-environment context of their usage and enable agents with heterogeneous abilities to act and to reason about action. We define a formal model for the contextual exposure of signifiers in hypermedia environments that aims to drive affordance exploitation. We demonstrate our approach with a prototypical Web-based MAS where two agents with different reasoning abilities proactively discover how to interact with their environment by perceiving only the signifiers that fit their abilities. We show that signifier exposure based on the dynamic agent-environment context helps to facilitate effective and efficient interactions on the Web.Type: conference paper