Study on the adaptation with learning about the environment: The case of post-acquisition integration

Jing Su (Corresponding Author), Mohsen Jafari Songhori, Takao Terano

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Organizations can be considered as complex systems that can adapt to their changing environment. In this work, we study a complex system adapting to an unfamiliar environment with learning; this is grounded in the context of the post-acquisition integration of the companies. More specifically, we conceptualize post-acquisition integration from the perspective of behavioral theory as a reason for the environmental changes to the firms (agents). We studied the adaptation of these complex systems and we propose a coupled learning method over the NK landscape. The simulation results show that the initial perceptions of the agents regarding the new task environment can be quite influential to the performance of the entire system during the adaptation process. Correct initial perceptions can help the system to quickly achieve high performance, whereas incorrect initial perceptions may prevent the system from reaching high performance. Lack of initial perceptions could lead to a slow yet robust adaptation process with a moderate level of performance. Moreover, certain other factors, such as the sensitivity to the feedback from the environment, the incentive of the system for exploration, and the learning frequency, may have different impact on the adaptation and performance of the system.

Original languageEnglish
Pages (from-to)640-653
Number of pages14
JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
Issue number5
Publication statusPublished - 1 Sept 2018


  • Agent-based simulation
  • Complex systems
  • Learning
  • Post-acquisition integration
  • Adaptation


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