Systematic Comparison of Software Agents and Digital Twins: Differences, Similarities, and Synergies in Industrial Production
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Abstract (arXiv)
To achieve a highly agile and flexible production, it is envisioned that industrial production systems gradually become more decentralized, interconnected, and intelligent. Within this vision, production assets collaborate with each other, exhibiting a high degree of autonomy. Furthermore, knowledge about individual production assets is readily available throughout their entire life-cycles. To realize this vision, adequate use of information technology is required. Two commonly applied software paradigms in this context are Software Agents (referred to as Agents) and Digital Twins (DTs). This work presents a systematic comparison of Agents and DTs in industrial applications. The goal of the study is to determine the differences, similarities, and potential synergies between the two paradigms. The comparison is based on the purposes for which Agents and DTs are applied, the properties and capabilities exhibited by these software paradigms, and how they can be allocated within the Reference Architecture Model Industry 4.0. The comparison reveals that Agents are commonly employed in the collaborative planning and execution of production processes, while DTs typically play a more passive role in monitoring production resources and processing information. Although these observations imply characteristic sets of capabilities and properties for both Agents and DTs, a clear and definitive distinction between the two paradigms cannot be made. Instead, the analysis indicates that production assets utilizing a combination of Agents and DTs would demonstrate high degrees of intelligence, autonomy, sociability, and fidelity. To achieve this, further standardization is required, particularly in the field of DTs.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 3 of its 248 references that are in the map. First posted on arXiv 17 Jul 2023.
Builds on
3 of 248 references.
References · 3
- 2021A Resilient and Energy-Aware Task Allocation Framework for Heterogeneous Multi-Robot Systemscited by 5
- 2018Classification of cyber-physical production systems applications: Proposition of an analysis frameworkcited by 1
- 2021Hybrid Digital Twin for process industry using Apros simulation environmentcited by 1
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Citing papers per year: 2024: 2; 2025: 0; 2026: 3.
5 papers.
- 2024Integrating Ontology Design with the CRISP-DM in the context of Cyber-Physical Systems Maintenancecited by 4
- 2026From Detection to Action: Using LLM Agents for Fault-Tolerant Controlcited by 2
- 2026Foundation-Model-Based Agents in Industrial Automation: Purposes, Capabilities, and Open Challengescited by 1
- 2024Cost Optimized Scheduling in Modular Electrolysis Plantscited by 0
- 2026Market Strategy Evaluation for Prosumers in Local Electricity Marketscited by 0
- 2026From Detection to Action: Using LLM Agents for Fault-Tolerant Control26 Jun 2026
- 2026Market Strategy Evaluation for Prosumers in Local Electricity Markets12 Jun 2026
- 2026Foundation-Model-Based Agents in Industrial Automation: Purposes, Capabilities, and Open Challenges4 May 2026
- 2024Integrating Ontology Design with the CRISP-DM in the context of Cyber-Physical Systems Maintenance9 Jul 2024
- 2024Cost Optimized Scheduling in Modular Electrolysis Plants7 Feb 2024