Open information systems semantics for distributed artificial intelligence
Artificial Intelligence
Lurker demographics: counting the silent
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Software engineering: a roadmap
Proceedings of the Conference on The Future of Software Engineering
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Thinking Objectively: The problem with scalability
Communications of the ACM
Case-Based Reasoning: Experiences, Lessons and Future Directions
Case-Based Reasoning: Experiences, Lessons and Future Directions
Naming the Unnamable: Socionics or the Sociological Turn of/to Distributed Artificial Intelligence
Autonomous Agents and Multi-Agent Systems
Infrastructure Issues and Themes for Scalable Multi-Agent Systems
Revised Papers from the International Workshop on Infrastructure for Multi-Agent Systems: Infrastructure for Agents, Multi-Agent Systems, and Scalable Multi-Agent Systems
Improving the Scalability of Multi-Agent Systems
Revised Papers from the International Workshop on Infrastructure for Multi-Agent Systems: Infrastructure for Agents, Multi-Agent Systems, and Scalable Multi-Agent Systems
Issues in Agent Communication: An Introduction
Issues in Agent Communication
Hi-index | 0.00 |
Internet communication is a major challenge for anyone claiming to design scalable multiagent systems. Millions of messages are passed every day, referring to one another and thus shaping a gigantic network of communication. In this paper, we compare and discuss two different approaches to modelling and analysing such large-scale networks of communication: Social Network Analysis (SNA) and Communication-Oriented Modelling (COM). We demonstrate that, with regard to scalability, COM offers striking advantages over SNA. Based on this comparison, we identify mechanisms that foster scalability in a broader sense, comprising issues of downscaling as well.