We investigate the use of Web agents that use planning to achieve goals involving preconditions on the dynamic Web. We implement our approach, AEPIS, based on Semantic Web technologies and rely on environmental information evaluated exclusively at runtime to take dynamic changes into account. We evaluate AEPIS in static and dynamic environments, based on the Web of Things, and compare its performance to a rule-based and an agent using large language models. We find that AEPIS combines adaptivity with rapid planning at scale, even in a dynamic environment.

This article introduces foundational components for decentralized B2B data sharing based on the solid protocol, emphasizing data sovereignty, security, and interoperability. These components are: (1) Authorization app (AuthApp) – facilitating granular control and compliance in access granting and revocation processes; (2) rights delegation proxy (RDP) – supporting controlled delegation of rights, enabling natural persons to act on behalf of organizations while ensuring privacy and traceability; (3) data provisioning proxy (DPP) – allowing seamless and secure data provisioning across organizations while masking the identity of upstream data sources to protect business interests. The components enable the creation of end-to-end, standards-based, flexible data value chains. We validate their applicability through a real-world financial services use case involving loan processing, which illustrates data sharing and protection challenges in B2B ecosystems.

We present our research project on distributed, agent-based control in dynamic environments. We motivate the usage of agents and their difficulties in dynamic environments like the Web, and relate this to the fields of distributed and agent-based systems. We describe our idea of lightweight strategies for agents to adapt behavior on disturbances without relying on centralized mechanisms, and outline objectives and challenges of our project. Finally, we explain our simulation experiments as research method, and discuss our initial results to design distributed, lightweight, scalable agents for dynamic environments.