1,721,035 research outputs found
Stigmergy-based parasitic strategies in architectural design for the transformation of existing heritage
Full text linkThe refurbishment of an abandoned post-WWII factory becomes a case study to propose an alternative approach to Italy’s mainstream preservation logics through parasitic architecture. Drawing from the fields of stigmergy-based systems, swarm intelligence and Embodied Embedded Cognition, their characterizing features and processes have been coded into a digital ecosystem where multi-agent systems operate. The project exploits the ecosystem and develops through strategies based on intrusion, adaptation and growth focusing on the relationships between different systems (host/parasite); the goal is to turn the present building (which has become an urban landmark for a socially intricate community) into a polarizing element for the community that facilitates its cultural expression by working on the material and spatial substrate as its prerequisites
Architectural Assemblages as Computational Medium: Introducing Assembler, a tool for the design and study of architectural assemblages
Full text linkAssembler is a computational tool designed for the creation and study of assemblages in architecture, interweaving mereology, combinatorial design, and decision at scale. The tool leverages the potential of automation and repeated parts to generate scalable and spatially heterogeneous assemblages, emphasizing the computational role of both parts and relations in creating emergent qualities. Assembler utilizes iterative, rule-based heuristic, enabling computation across scales via part/assemblage/environment relationhood. The design process is understood as a decision network, where the user has control over the design of parts, connections, and heuristics of the system, and the tool enacts those decisions in space and time. After a theoretical contextualization and an overview of precursors and precedents in architecture and combinatorial design, the tool logic is explained and its current status and potential developments are discusse
Aesthetics of Decision - Unfolding the design process within a framework of complexity and self-organization
Full text linkComplexity-grounded paradigms and self-organization based strategies promise enormous potential when channeled in a design process, but their current stage of development (while delivering groundbreaking results in recent years) hasn't significantly impacted yet the widespread architectural practice. Still, the tendency (in the development of technology and society) is clearly towards an increase in complexity and distributed intelligence, henceforth it is of primary importance to adopt a design approach that allows the harnessing of such potential and convey it in the creation of outcomes that favor a richer and heterogeneous ecological entanglement. To tap this kind of potential in an open-ended process requires a design approach that re-defines the distribution of control, choices and information throughout the whole process (including materials and fabrication processes).The paper explores the possibility of such design approach in the territory that links education and research through a series of Master Thesis developed at the University of Bologna and comparing them to other case studies developed worldwide
The Red Queen Hypothesis - Chemotaxic stigmergic systems and Embodied Embedded Cognition-based strategies in architectural design
Full text linkCognitive Assemblages: Spatial Generation Through Wave Function Collapse and Reinforcement Learning
No full textThis research explores the integration of AI in an iterative decision process for the open-ended procedural generation of architectural spaces. Leveraging on state-of-the-art Deep Reinforcement Learning techniques, an Artificial Neural Network (ANN) is trained to perform local decisions selecting tiles in a Wave Function Collapse (WFC) algorithm, assembling discrete elements that build up a complex spatial organization, pursuing selected spatial qualities at the architectural scale
Training Spaces - Fostering machine sensibility for spatial assemblages through wave function collapse and reinforcement learning
No full textThis research explores the integration of Deep Reinforcement Learning (RL) and a Wave Function Collapse (WFC) algorithm for a goal-driven, open-ended generation of architectural spaces. Our approach binds RL to a distributed network of decisions, unfolding through three key steps: the definition of a set of architectural components (tiles) and their connectivity rules, the selection of the tile placement location, which is determined by the WFC, and the choice of which tile to place, which is performed by RL. The act of thinking becomes granular and embedded in an iterative process, distributed among human and non-human cognition, which constantly negotiate their agency and authorial status. Tools become active agents capable of developing their own sensibility while controlling specific spatial conditions. Establishing an interdependency with the human, that engenders the design patterns and becomes an indispensable prerequisite for the exploration of the generated design space, exceeding human or machinic reach alone
Homeorhetic Assemblies - Turning beehive formation dynamics into high-res tectonics
No full textThis thesis research investigates the architectural and tectonic potential that can stem from behavioral complexity of collective construction in biological systems and its dynamic relations with the colony in terms of the continuous construction and adaptation process over the time. The role model considered as a case study regards the dynamics of honeycomb formation, and in particular three fundamental behaviours have been extracted from this biological process: stigmergic behavior, structural self-stabilization capacity and environmental adaptability. All these features were then coded into a multi agent system interacting in an heterogeneous environment and capable of selectively adding elements to a particle-spring system that is periodically self-adjusting, simulating material behavior. The outcomes, strongly rich and heterogeneous in their spatial organization, are characterized by a continuous tectonic of emerging singularities seamlessly flowing into one another
Homeostatic patterns
No full textHomeostasis is the condition where a system reaches a dynamic balance: biological systems exhibit typical self-regulatory dynamics for morphogenetic processes that thrive on matter's self-organization capacity through which it exhibits hierarchy and organization and which is responsible for the optimization processes that guide the efficient use of energy. Optimization is aimed to achieve local efficiency of multiple goals processes with divergent demands, which are negotiated by a prevalence principle where non-prevalent demands do not cease to exist (as in exclusivity principle) but modify themselves serving the prevailing ones (their domain of expression is constrained by the paths traced in the prevailing demand's one). The goal of this paper is to show how such processes can be translated through a specific case study application in architecture: as in biological organisms, in this project matter and energy exchanges are regulated by integrated efficient systems rather than assemblies of monooptimized elements. �� 2013 Taylor & Francis Group
Computational morphogenesis in architecture: Structure and light as a multi-objective design/optimization problem
No full textThis paper deals with a multi-objective design/optimization problem of grid-shells, meant to evaluate, as fitness function, structural behavior together with light absorption/shading. Such performance criteria separately bring to different and divergent optimal solutions, while considered as a whole are expected to result in several equivalent or similar suboptimal shapes. With the aid of a Genetic Algorithm (GA), this multi-objective optimization problem is here performed to explore and search for suitable solutions - it becomes a design tool more than a solution one. Three benchmarks have been developed before a more complex application on an existing case study - the Esplanade in Singapore by DP Architects (DPA) and Michael Wilford & Partners (MWP). �� 2013 Taylor & Francis Group
Modeling the resituation of memory in neurobiology and narrative
No full textIn narrative and neurobiological processes, a common response to an unexpected event can be observed: retroactive reinterpretation. In this activity, an established state of knowledge is restructured so that its ability to interpret causal consequences changes. We present a new graphical knowledge modeling technique to track the stages of retroactive reinterpretation in both narrative and biological domains. This method is based on situation-theoretic foundations, which have been extended using narrative devices to capture elusive properties of everyday reasoning, such as context and causal anticipation. The method and its accompanying visual model enables us to experiment with representational reasoning about cause, shifts in influence between distinct systems and implicit knowledge. This work-in-progress indicates that cross-system, multi-ontology intelligence processes can be modeled using narrative mechanisms. A future goal is to use this method to address problems in ontological interoperability for predictive, multi-system neurobiological modeling. Capturing implicit causal agency in biology using a narrative-based model is thus feasible but comes with challenges in graphical display, which are discussed
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