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[2512.17979] Adaptive Agents in Spatial Double-Auction Markets: Modeling the Emergence of Industrial Symbiosis
Summary
This paper presents an agent-based model to explore how adaptive agents in spatial double-auction markets can foster industrial symbiosis by optimizing resource exchanges among firms.
Why It Matters
Understanding the dynamics of industrial symbiosis is crucial for promoting sustainable practices in industries. This research highlights how spatial structures and adaptive behaviors can enhance market efficiency and support sustainability goals, providing insights for policymakers and businesses alike.
Key Takeaways
- The model demonstrates how firms can adapt their strategies in a spatially embedded market to optimize resource exchanges.
- Simulation results reveal conditions under which decentralized exchanges achieve stable and efficient outcomes.
- The research underscores the importance of spatial structures in facilitating industrial symbiosis and circular economy practices.
- Counterfactual analysis indicates that sellers' strategies can approach a near Nash equilibrium, enhancing market efficiency.
- The findings provide a foundation for exploring policy interventions that align firm incentives with sustainability objectives.
Computer Science > Computer Science and Game Theory arXiv:2512.17979 (cs) [Submitted on 19 Dec 2025 (v1), last revised 16 Feb 2026 (this version, v2)] Title:Adaptive Agents in Spatial Double-Auction Markets: Modeling the Emergence of Industrial Symbiosis Authors:Matthieu Mastio, Paul Saves, Benoit Gaudou, Nicolas Verstaevel View a PDF of the paper titled Adaptive Agents in Spatial Double-Auction Markets: Modeling the Emergence of Industrial Symbiosis, by Matthieu Mastio and Paul Saves and Benoit Gaudou and Nicolas Verstaevel View PDF HTML (experimental) Abstract:Industrial symbiosis fosters circularity by enabling firms to repurpose residual resources, yet its emergence is constrained by socio-spatial frictions that shape costs, matching opportunities, and market efficiency. Existing models often overlook the interaction between spatial structure, market design, and adaptive firm behavior, limiting our understanding of where and how symbiosis arises. We develop an agent-based model where heterogeneous firms trade byproducts through a spatially embedded double-auction market, with prices and quantities emerging endogenously from local interactions. Leveraging reinforcement learning, firms adapt their bidding strategies to maximize profit while accounting for transport costs, disposal penalties, and resource scarcity. Simulation experiments reveal the economic and spatial conditions under which decentralized exchanges converge toward stable and efficient outcomes. Counterfac...
