New Coevolution Dynamic as an Optimization Strategy in Group Problem Solving
Abstract
In society, it is common to face problems that require collaboration with other people, from everyday challenges to complex tasks, such as group projects at work. In this context, the search for more effective problem-solving strategies becomes a topic of great interest. This paper presents a new dynamic that integrates coevolution into the NK model together with an Erdös-Rényi random network, allowing more than one neighbor update. We explore how this coevolution can be employed as an optimization strategy for solving group problems. In recent coevolution models, only one agent is removed and another is added to the neighborhood of influence. Here, we allow $L$ agents to be changed, which had a large impact on the system performance. In the analysis of the results, we consider rewiring as a way for the target agent to obtain information from individuals or groups that were not part of its neighborhood. Our simulations demonstrate that coevolution can produces gain on the computational cost.
- Publication:
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arXiv e-prints
- Pub Date:
- August 2024
- DOI:
- 10.48550/arXiv.2408.06434
- arXiv:
- arXiv:2408.06434
- Bibcode:
- 2024arXiv240806434F
- Keywords:
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- Nonlinear Sciences - Chaotic Dynamics;
- Physics - Physics and Society
- E-Print:
- 9 pages, 8 figures