The aim of this paper is to discuss that media is not only changing the way architecture is represented, but also the way it is produced, reproduced and consumed. It is the originality of the paper to discuss Instagram and Archigram to focus on the changing relationship between media and architecture. With advances in information and communication technology, media is now expanding into digital media and social media. Computer technology supports media to be re-generated in a new environment. Media is accordingly re-generating architecture. The constant flow of images, particularly on social media platforms, such as Instagram, leads to architecture being seen and understood as an image production. The paper argues that Instagram (non-printed) and Archigram (printed) refer to architecture without architecture. They provide a specific medium for architecture to construct not buildings, but images of buildings. Instagram is not an alternative to Archigram, but both allow images to dominate text and objects in architecture. Although media is changing radically, architecture still represents and reproduces itself through media. It is therefore crucial to understand the dynamics and realities of media to understand the reality of architecture.

This study combines multi-agent systems and Deleuzian thought with an interdisciplinary approach, aiming to bring together the explanatory world of the natural sciences and the world of meanings of the social sciences. The study first analyzes the conceptual framework of Deleuzian thought and the working mechanisms of swarm behaviors in multi-agent-based systems. In this context, the concepts of machine, assemblage, rhizome, and flow, which appear in the Deleuzian thought system of the twentieth-century French philosophers Gilles Deleuze and Felix Guattari, were focused on mainly. Subsequently, the relationships between Deleuzian thought and multi-agent systems are examined and interpreted through animated representations created using the Java language in Processing, a graphical programming software. After scrutinizing the representations created in the study, it was concluded that multi-agent systems are compatible with this system of thought, as agents themselves are capable of incorporating the concepts of Deleuzian thought within their working mechanisms. In this regard, the study concluded that multi-agent systems can be considered as ontological frameworks, philosophical systems of thought. Here, the study contributes to social sciences and design research by offering a computationally grounded lens through which concepts of a thought system can be represented, observed, and interpreted in action. By demonstrating how multi-agent systems embody machinic assemblages, emergent flows, and rhizomatic relations, the study provides a methodological approach that enables philosophical concepts and contemporary social theories to inform structure and inspire new forms of creative and analytical inquiry.

This study repositions the concept of tolerance in digital space production not only as a technical flexibility but also as an ontological and algorithmic openness. In contrast to representational, form-centered and deterministic design approaches, it advocates an understanding of space established through interaction, process and difference. Drawing on Gilles Deleuze’s idea of becoming and difference and Luciana Parisi’s computational aesthetic approach, the research conceptualizes digital space not as a fixed structure but as a constantly emerging area of relationality. In this context, tolerance is not considered as an error or deviation but as a productive area of uncertainty inherent in the evolutionary nature of digital systems.

Experiments conducted within the framework of agent-based systems reveal how tolerance operates on behavioral, formal and temporal planes. In these systems, where parameters are defined not with definite values but with intervals, space emerges not from form but from interaction. The study proposes a new architectural way of thinking that distances digital design from certainty and approaches uncertainty with openness. As a result, tolerance is considered not only as a technical aspect but also as an ethical and creative design principle in digital architecture.

The aim of this article is to examine how creative agency in architectural design has transformed in the context of the second digital turn, through interactions between architects and digital environments in generative design settings. It discusses how the human-centered notion of the creative subject, grounded in the Renaissance figure of the “quasi-divine creative architect,” has been challenged by generative algorithms, parametric modeling, and digital fabrication technologies, redefining creative agency as a hybrid “co-creative agent.” The theoretical framework is structured around three axes: (i) Margaret Boden’s approach to creativity, defining it through novelty, surprise, and value, and through combinational, exploratory, and transformational modes; (ii) literature on human–computer co-creativity, including concepts such as human–computer symbiosis, creative provocateur, curator architect, hybrid intelligence, and composite subject; and (iii) 4E cognition theories (embedded, embodied, extended, and enactive), which conceptualize cognition as distributed across body, tools, environment, and action. Together, these axes support the argument that creative agency does not reside in a single mind but emerges relationally across the architect–digital environment–material–production technology network. The study adopts a research-through-design approach that treats design as a mode of knowledge production. An installation produced for the International Architecture Biennial 2025 [institution omitted for blind review] served as both site and research instrument. Interaction processes between the researcher-architect and Rhino–Grasshopper, a differential growth algorithm, AI-assisted visualization tools, and multi-scale 3D printing technologies were documented throughout the process. The resulting dataset—design journals, digital process logs, visual documentation, and technical notes—was analyzed using reflexive qualitative methods, timeline mapping, and thematic analysis. The findings show that the design thinking embodied in the installation satisfies Boden’s criteria of novelty, surprise, and value. Reproducing the traditional abundance motif through a differential growth algorithm enabled: at the combinational level, the unexpected fusion of a familiar motif with organic algorithmic patterns; at the exploratory level, the investigation of new formal spaces through parametric variation; and at the transformational level, the generation of previously impossible forms by rewriting the motif’s defining rules. From a 4E cognition perspective, the process is revealed as embedded in context, shaped by body–tool interaction, extended through digital environments, and constituted through architect–algorithm action loops. The study argues that after the second digital turn, creative agency in architectural design has shifted from a singular human-centered activity toward a hybrid co-creative agent emerging from architect–digital environment interaction. By concretizing this hybrid agency in both process and spatial output, the installation demonstrates that design should be understood as a relational cognitive action enacted through reciprocal human–machine performance. Integrating differential growth–based generative design with parametric modeling and multi-scale 3D fabrication provides an original empirical contribution to the JCoDe special issue, advancing understanding of how cross-scale generative design intelligence is produced.

This study evaluates the performance of three AI models—Claude 3.5 Sonnet, Gemini 1.5 Flash, and ChatGPT 4o—in generating interior design outputs based on seven key design criteria: design style, color, lighting, furniture and product, interior materials, architectural features, and spatial layout. The evaluation was conducted across six different space designs, with 15 participants scoring the AI-generated outputs on a scale of 1 to 5. The results indicate that Claude 3.5 Sonnet achieved the highest overall performance due to its consistent scores across multiple criteria, followed closely by Gemini 1.5 Flash, which excelled in design style and color but exhibited slight variability. ChatGPT 4o, while demonstrating strong performance in furniture and lighting, struggled with inconsistencies, leading to its lower overall ranking. Despite their competitive performance, areas such as spatial layout and interior materials presented challenges for all models, highlighting opportunities for improvement. This study underscores the growing potential of AI in supporting design processes while emphasizing the need for further refinement and expansion to address limitations in complex spatial and material contexts.

This study aims to identify the effects of integrating artificial intelligence (AI) into design studio pedagogy by conducting a systematic review of recent research on the subject, with a particular focus on its impact on design processes, learning outcomes, and instructor–student interaction. To ensure a structured and replicable analysis, a systematic review methodology was adopted. Accordingly, the study was designed based on qualitative research methods, and the data were collected through keyword searches in Google Scholar, Scopus, and Web of Science using the following combinations: “artificial intelligence” AND “design studio pedagogy,” “AI in architectural education,” “AI-assisted design education,” “AI AND design education,” “studio-based learning” AND “AI,” “human-AI collaboration” AND “design studio.” After applying the inclusion criteria, 21 articles were selected to form the data set. These studies were categorized along four analytical dimensions: the role AI assumes in the studio, the scope of its influence, the design stage at which it is utilized, and the methodological approach of each study. The findings indicate that AI contributes to design studio environments across three main areas: (1) its role as an idea-generation partner; (2) its influence on learning outcomes and performance indicators, including changes in the design process, enhancement of creativity, and improved conceptualization skills; and (3) its support of the early conceptual stages within the design workflow. However, several studies note that using AI as an idea-generation partner does not always correspond to improved design quality or enhanced creativity. Similarly, while AI tools may accelerate workflow and increase time efficiency, this does not necessarily translate into higher-quality design outputs. In addition to these contributions, some studies highlight disadvantages such as maintaining design logic, integrating AI-generated outputs into coherent and conceptually consistent design ideas, and addressing ethical concerns. Furthermore, the data remain insufficient regarding AI’s role in supporting instructors within studio environments and its potential effects on instructor–student relationships. The results also emphasize that despite the rapid adoption of AI tools, current research largely consists of small-scale case studies or experimental workshop implementations, leading to fragmented and limited collective pedagogical insights. Therefore, more systematic and comprehensive evaluations are needed to better understand how AI influences design workflows, cognitive processes, student performance, and instructor–student dynamics. It is additionally necessary to investigate the long-term integration of AI across all stages of the design process rather than focusing solely on specific phases. The data presented in this study are significant in offering a systematic analysis of the use of AI tools in design studio environments. The findings are expected to provide a meaningful contribution to the field by establishing a framework for the integration of AI tools into design studio pedagogy

Floor covering materials are made for the purposes of protecting the floor layers, being functional and aesthetic, ensuring user safety and comfort. Therefore, in addition to determining the space and user needs well, the investment cost of the material, service life, durability, operating cost, comfort and environmental impact are effective factors in the decision-making phase. When covering materials with different properties are evaluated within the scope of these selection factors, they may have different advantages and disadvantages. In the selection of floor covering materials, it has great importance to consider these properties of the materials together and to make the most appropriate decision among the alternatives. It would be healthier to perform this process, which requires complex decision processes, on a more systematic and realistic level. Therefore, unlike the classical logical computer selection system that makes sharp evaluations as “correct (1)” and “incorrect (0), the fuzzy logic method, which is an approach that evaluates by considering many criteria together just like the human brain and can consider the deficiency in information, was chosen. In the study; it was aimed to create a more realistic decision process in the selection of floor coverings by evaluating the decision criteria in the selection of floor coverings in office spaces with the fuzzy logic approach. The selection criteria for floor covering materials (investment cost, service life, operating cost and environmental impact) and membership functions for materials commonly used in office flooring (wood, carpet, PVC and ceramics) were defined with fuzzy sets and the model was completed in line with the established rules. Then, 3 different scenarios were created based on the selection criteria, namely balanced, operating cost focused and environmental impact focused, and these scenarios were evaluated using the model created in the Matlab program. As a result of the evaluations, it was seen that wood was the most suitable choice among wood, PVC, carpet and ceramic flooring materials in all scenarios.