SPIDA: Abstracting and generalizing layout design cases

Abstraction and generalization of layout design cases generate new knowledge that is more widely applicable to use than specific design cases. The abstraction and generalization of design cases into hierarchical levels of abstractions provide the designer with the flexibility to apply any level of abstract and generalized knowledge for a new layout design problem. Existing case-based layout learning (CBLL) systems abstract and generalize cases into single levels of abstractions, but not into a hierarchy. In this paper, we propose a new approach, termed customized viewpoint - spatial (CV-S), which supports the generalization and abstraction of spatial layouts into hierarchies along with a supporting system, SPIDA (SPatial Intelligent Design Assistant)

Physically based mechanical metaphors in architectural space planning

Physically based space planning is a means for automating the conceptual design process by applying the physics of motion to space plan elements. This methodology provides for a responsive design process, allowing a designer to easily make decisions whose consequences propagate throughout the design. It combines the speed of automated design methods with the flexibility of manual design methods, while adding a highly interactive quality and a sense of collaboration with the design. The primary assumption is that a digital design tool based on a physics paradigm can facilitate the architectural space planning process. The hypotheses are that Newtonian dynamics can be used 1) to define mechanical metaphors to represent the elements in an architectural space plan, 2) to compute architectural space planning solutions, and 3) to interact with architectural space plans. I show that space plan elements can be represented as physical masses, that design objectives can be represented using mechanical metaphors such as springs, repulsion fields, and screw clamps, that a layout solution can be computed by using these elements in a dynamical simulation, and that the user can interact with that solution by applying forces that are also models of the same mechanical objects. I present a prototype software application that successfully implements this approach. A subjective evaluation of this prototype reveals that it demonstrates a feasible process for producing space plans, and that it can potentially improve the design process because of the quality of the manipulation and the enhanced opportunities for design exploration it provides to the designer. I found that an important characteristic of this approach is that representation, computation, and interaction are all defined using the same paradigm. This contrasts with most approaches to automated space planning, where these three characteristics are usually defined in completely different ways. Also emerging from this work is a new cognitive theory of design titled 'dynamical design imagery,' which proposes that the elements in a designer's mental imagery during the act of design are dynamic in nature and act as a dynamical system, rather than as static images that are modified in a piecewise algorithmic manner

Automated space layout planning for environmental sustainability

There is a growing global interest in low/zero carbon buildings in response to the increased CO2 in the atmosphere, nearly half of which comes from building energy consumption. Buildings are built for a considerably longer lifespan and enhancing energy efficiency in buildings can play a significant role in reducing CO2 emissions. Energy efficiency features need to be incorporated at the earliest, as alterations to the design at latter stages may prove to be difficult and sometimes expensive. Building design is concerned with satisfying various objectives (e.g. cost, efficiency of a space layout, energy consumption), which are sometimes in conflict with each other. Performance of various indicators, therefore, needs to be assessed as a whole rather than in isolation. Space layout planning is considered as the starting point of building design. Most performance indicators; i.e. cost, energy efficiency, etc. are closely linked with the layout. Researchers have attempted at automating space layout planning since the 1960s with a view to effectively search the solution space. Diverse approaches are adopted in space layout planning that ranges from the analysis of spatial proximity to the application of ‘space syntax’ theory. Developments in whole building energy simulation and integration of simulation in the design process imply that the search for optimum space layout could be better guided by incorporating detailed-based simulation as response generators as opposed to the ones with a simplified representation of the problem domain. This paper describes a framework for sustainable space layout planning that uses evolutionary computation methods to search the solution space. Whole building simulation programs are used as response generators to guide the search for energy efficient layouts. The integrated approach enables the consideration of energy consumption, in addition to the geometry and topology, for decision making during space layout planning

Interactive constraint-based space layout planning

Layout planning is the primordial design activity that determines the characteristics and performance of a building throughout its lifecycle. Due to its iterative nature, there is a growing interest in the automation of space layout planning to enhance the search for optimum design solutions. The approaches for automation range from constraint/heuristics-based to the application of numerical optimisation algorithms. Among these, the use of design constraints to guide the search of the solution space is well regarded due to its ability to model design problems of an applied nature with multiple objectives. Constraint-based approaches also allow interactivity between the designer and layout planning process, which simulates the iterative nature of creative design and can be integrated well with the existing design process. Interactivity also enhances the management of design knowledge through improved processing and visualisation of information. This paper presents a theoretical framework for interactive constraint-based layout optimisation with an implemented prototype for a hospital patient room interior layout. The theoretical framework was developed by analysing existing layout automation methods and interactive approaches through a review of relevant literature. Object-oriented computer programming was used to develop the prototype to demonstrate the proposed approach of interactive layout planning system. The framework augments the iterative design process by facilitating the active participation and sharing of the designer’s knowledge during the aggregation. With regard to the implementation of the framework in large problems, fast evaluation of design solution was found to be necessary to interact with the system in real time. Interactive constraint-based layout optimisation has, therefore, the ability to enhance the search process of optimum design solutions by augmenting the iterative nature of the creative design process

Integrated Reconfigurable Autonomous Architecture System

Advances in state-of-the-art architectural robotics and artificially intelligent design algorithms have the potential not only to transform how we design and build architecture, but to fundamentally change our relationship to the built environment. This system is situated within a larger body of research related to embedding autonomous agency directly into the built environment through the linkage of AI, computation, and robotics. It challenges the traditional separation between digital design and physical construction through the development of an autonomous architecture with an adaptive lifecycle. Integrated Reconfigurable Autonomous Architecture System (IRAAS) is composed of three components: 1) an interactive platform for user and environmental data input, 2) an agent-based generative space planning algorithm with deep reinforcement learning for continuous spatial adaptation, 3) a distributed robotic material system with bi-directional cyber-physical control protocols for simultaneous state alignment. The generative algorithm is a multi-agent system trained using deep reinforcement learning to learn adaptive policies for adjusting the scales, shapes, and relational organization of spatial volumes by processing changes in the environment and user requirements. The robotic material system was designed with a symbiotic relationship between active and passive modular components. Distributed robots slide their bodies on tracks built into passive blocks that enable their locomotion while utilizing a locking and unlocking system to reconfigure the assemblages they move across. The three subsystems have been developed in relation to each other to consider both the constraints of the AI-driven design algorithm and the robotic material system, enabling intelligent spatial adaptation with a continuous feedback chain

Proceedings of the ECCS 2005 satellite workshop: embracing complexity in design - Paris 17 November 2005

Embracing complexity in design is one of the critical issues and challenges of the 21st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr). Embracing complexity in design is one of the critical issues and challenges of the 21st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr)