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Multiagent Systems (MAS) research reached a maturity to be confidently applied to real-life complex problems. Successful application of MAS methods for behavior modeling, strategic reasoning, and decentralized governance, encouraged us to focus on applicability of MAS techniques in a class of industrial systems and to elaborate on potentials and challenges for method integration/contextualization. We direct attention towards a form of industrial practices called Industrial Symbiosis Systems (ISS) as a highly dynamic domain of application for MAS techniques. In ISS, firms aim to reduce their material and energy footprint by circulating reusable resources among the members. To enable systematic reasoning about ISS behavior and support firms (as well as ISS designers) decisions, we see the opportunity for marrying industrial engineering with engineering multiagent systems. This enables introducing (1) representation frameworks to reason about dynamics of ISS, (2) operational semantics to develop computational models for ISS, and (3) coordination mechanisms to enforce desirable ISS behaviors. We argue for applicability and expressiveness of resource-bounded formalisms and norm-aware mechanisms for the design and deployment of ISS practices. In this proposal, we elaborate on different dimensions of ISS, present a methodological foundation for ISS development, and finally discuss open problems.
We present a formal multiagent framework for coordinating a class of collaborative industrial practices called Industrial Symbiotic Networks (ISNs) as cooperative games. The game-theoretic formulation of ISNs enables systematic reasoning about what w
This paper discusses the dynamics of Transaction Cost (TC) in Industrial Symbiosis Institutions (ISI) and provides a fair and stable mechanism for TC allocation among the involved firms in a given ISI. In principle, industrial symbiosis, as an implem
Modeling agent behavior is central to understanding the emergence of complex phenomena in multiagent systems. Prior work in agent modeling has largely been task-specific and driven by hand-engineering domain-specific prior knowledge. We propose a gen
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