Multi-agent learning is a crucial method to control or find solutions for systems, in which more than one entity needs to be adaptive. In today's interconnected world, such s...
The paper presents peer-to-peer multi-agent framework for community clustering based on contact propagation in the global network of contacts with individual ontology-based descrip...
In this work we present the basic concepts for a dynamic plug-in-based software architecture using concepts from the Petri net-based MAS framework Mulan. By transferring the conce...
Lawrence Cabac, Michael Duvigneau, Daniel Moldt, H...
Open trading environments involve a type of peer-to-peer computing characterised by well-defined interaction protocols that are used by the traders and sometimes updated dynamicall...
Martin K. Purvis, Mariusz Nowostawski, Stephen Cra...
This paper unifies two recent strands of research in multiagent system design. One, commitments are widely recognized as capturing important aspects of interactions among agents,...