@misc{13577,
  abstract     = {{Background
Individuals with borderline personality disorder (BPD) frequently alter between idealizing and devaluing other persons, which has been linked to an increased tendency to update self-relevant beliefs and impressions. We hypothesized that increased impression updating could stem from reduced attitude contextualization, i.e., a process in which impression-disconfirming information is linked to contextual cues.
Methods
Individuals diagnosed with BPD and controls (recruited online, with unknown diagnostic status) completed an impression formation paradigm. They first learned about the positive or negative behaviors of others in one Context A (e.g., Person 1 is helpful), followed by learning about behaviors of the opposite valence in a second Context B (Person 1 is rude). We also manipulated between participants whether the observed behaviors were directed toward the study participants (self-relevant) or, more generally, at other people (other-relevant). The contexts were marked by differently-colored backgrounds (e.g., yellow vs. blue), to avoid influences of prior knowledge or experiences. After exposure to information in both contexts, participants rated their impressions of the persons in Context A, Context B, and, crucially, a previously unknown Context C (white background). We examined whether the initial or an updated impression (re-)emerged in Context C.
Results
Initial impressions remained stable and dominated the ratings of controls across contexts A, B, and C for both self-relevant and other-relevant behaviors, consistent with contextualizing impression-disconfirming information. As expected, however, individuals with BPD only showed updated impression ratings in Context C for self-relevant behaviors, consistent with the assumed reduced tendency to contextualize impression-disconfirming self-relevant information. Further exploratory analyses suggest that more severe BPD symptoms predicted more pronounced impression updating in the self-relevant condition.
Conclusions
The findings help to illuminate the mechanisms underlying interpersonal problems in individuals with BPD. People with BPD are not just more inclined to discard positive first impressions but to re-evaluate disliked others when they behave positively, contributing to the volatility of interactions with others. Contextualization has known and modifiable antecedents, and the study may thus provide potential targets for therapeutic intervention. Future studies will need to replicate the findings with specified controls.}},
  author       = {{Konegen, Kevin and Halbeisen, Georg and Paslakis, Georgios}},
  booktitle    = {{Borderline Personality Disorder and Emotion Dysregulation}},
  issn         = {{2051-6673}},
  keywords     = {{Borderline personality disorder, Interpersonal problems, Social cognition, Belief updating, Renewal, Impression formation, Attitudes, Psychotherapy}},
  number       = {{1}},
  publisher    = {{BioMed Central}},
  title        = {{{A second chance for first impressions: evidence for altered impression updating in borderline personality disorder}}},
  doi          = {{10.1186/s40479-024-00259-y}},
  volume       = {{11}},
  year         = {{2024}},
}

@misc{13636,
  abstract     = {{Successful treatment not only depends on adhering to taking medication and attending therapy but also on behavioral changes. In two experiments (total N = 256), we investigated the hypothesis that the perceived social role of a treatment as partner (co-producer of a health-benefits) or servant (sole provider of health benefits) could promote or prevent intentions to engage in health-related behaviors. Specifically, we used headache treatment as an everyday example and found that participants were more inclined to engage in headache-reducing behaviors when painkillers were described as partners as compared to servants. Implications of these findings for the importance of anthropomorphic social perception in the clinical application are discussed. }},
  author       = {{Aengenheister, Jana S. and Urban, Renée and Halbeisen, Georg}},
  booktitle    = {{Zeitschrift für Psychologie}},
  issn         = {{2151-2604}},
  keywords     = {{social cognition, health behavior, anthropomorphism, headache}},
  number       = {{3}},
  pages        = {{171--177}},
  publisher    = {{Hogrefe }},
  title        = {{{Cures That (Make You) Work How a Treatment's Social Role Affects Health-Related Behavioral Intentions}}},
  doi          = {{10.1027/2151-2604/a000449}},
  volume       = {{229}},
  year         = {{2021}},
}

@misc{12800,
  abstract     = {{his paper presents the cognitive module of the Cognitive Architecture for Artificial Intelligence (CAAI) in cyber-physical production systems (CPPS). The goal of this architecture is to reduce the implementation effort of artificial intelligence (AI) algorithms in CPPS. Declarative user goals and the provided algorithm-knowledge base allow the dynamic pipeline orchestration and configuration. A big data platform (BDP) instantiates the pipelines and monitors the CPPS performance for further evaluation through the cognitive module. Thus, the cognitive module is able to select feasible and robust configurations for process pipelines in varying use cases. Furthermore, it automatically adapts the models and algorithms based on model quality and resource consumption. The cognitive module also instantiates additional pipelines to evaluate algorithms from different classes on test functions. CAAI relies on well-defined interfaces to enable the integration of additional modules and reduce implementation effort. Finally, an implementation based on Docker, Kubernetes, and Kafka for the virtualization and orchestration of the individual modules and as messaging technology for module communication is used to evaluate a real-world use case.}},
  author       = {{Strohschein, Jan and Fischbach, Andreas and Bunte, Andreas and Faeskorn-Woyke, Heide and Moriz, Natalia and Bartz-Beielstein, Thomas}},
  booktitle    = {{The International Journal of Advanced Manufacturing Technology}},
  issn         = {{1433-3015}},
  keywords     = {{Cognition, Industry 40, Big data platform, Machine learning, CPPS, Optimization, Algorithm selection, Simulation}},
  number       = {{11-12}},
  pages        = {{3513--3532}},
  publisher    = {{Springer }},
  title        = {{{Cognitive capabilities for the CAAI in cyber-physical production systems}}},
  doi          = {{10.1007/s00170-021-07248-3}},
  volume       = {{115}},
  year         = {{2021}},
}

@article{4518,
  abstract     = {{This paper introduces CAAI, a novel cognitive architecture for artificial intelligence in cyber-physical production systems. The goal of the architecture is to reduce the implementation effort for the usage of artificial intelligence algorithms. The core of the CAAI is a cognitive module that processes the user's declarative goals, selects suitable models and algorithms, and creates a configuration for the execution of a processing pipeline on a big data platform. Constant observation and evaluation against performance criteria assess the performance of pipelines for many and different use cases. Based on these evaluations, the pipelines are automatically adapted if necessary. The modular design with well-defined interfaces enables the reusability and extensibility of pipeline components. A big data platform implements this modular design supported by technologies such as Docker, Kubernetes, and Kafka for virtualization and orchestration of the individual components and their communication. The implementation of the architecture is evaluated using a real-world use case. The prototypic implementation is accessible on GitHub and contains a demonstration.}},
  author       = {{Fischbach, Andreas and Strohschein, Jan and Bunte, Andreas and Stork, Jörg and Faeskorn-Woyke, Heide and Moriz, Natalia and Bartz-Beielstein, Thomas}},
  issn         = {{1433-3015}},
  journal      = {{The International Journal of Advanced Manufacturing Technology}},
  keywords     = {{CPPS, Artificial intelligence, Industry 40, Reference architecture, Optimization, SMBO, Cognition, Big data platform, Modularization, AutoML}},
  number       = {{1/2}},
  pages        = {{609--626}},
  publisher    = {{Springer}},
  title        = {{{CAAI -- A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems}}},
  doi          = {{10.1007/s00170-020-06094-z}},
  volume       = {{111}},
  year         = {{2020}},
}

@inproceedings{4781,
  abstract     = {{Cyber-physical production systems (CPPS) integrate physical and computational resources due to increasingly available sensors and processing power. This enables the usage of data, to create additional benefit, such as condition monitoring or optimization. These capabilities can lead to cognition, such that the system is able to adapt independently to changing circumstances by learning from additional sensors information. Developing a reference architecture for the design of CPPS and standardization of machines and software interfaces is crucial to enable compatibility of data usage between different machine models and vendors. This paper analysis existing reference architecture regarding their cognitive abilities, based on requirements that are derived from three different use cases. The results from the evaluation of the reference architectures, which include two instances that stem from the field of cognitive science, reveal a gap in the applicability of the architectures regarding the generalizability and the level of abstraction. While reference architectures from the field of automation are suitable to address use case specific requirements, and do not address the general requirements, especially w.r.t. adaptability, the examples from the field of cognitive science are well usable to reach a high level of adaption and cognition. It is desirable to merge advantages of both classes of architectures to address challenges in the field of CPPS in Industrie 4.0.}},
  author       = {{Bunte, Andreas and Fischbach, Andreas and Strohschein, Jan and Bartz-Beielstein, Thomas and Faeskorn-Woyke, Heide and Niggemann, Oliver}},
  booktitle    = {{24nd IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)}},
  isbn         = {{978-1-7281-0303-7}},
  issn         = {{1946-0759}},
  keywords     = {{Reference Architecture, Cognition, Industrie 4.0}},
  location     = {{Zaragoza, SPAIN}},
  pages        = {{729--736}},
  publisher    = {{IEEE}},
  title        = {{{Evaluation of Cognitive Architectures for Cyber-Physical Production Systems}}},
  doi          = {{10.1109/etfa.2019.8869038}},
  year         = {{2019}},
}