96,688 research outputs found
Design thinking support: information systems versus reasoning
Numerous attempts have been made to conceive and implement appropriate information systems to support architectural designers in their creative design thinking processes. These information systems aim at providing support in very diverse ways: enabling designers to make diverse kinds of visual representations of a design, enabling them to make complex calculations and simulations which take into account numerous relevant parameters in the design context, providing them with loads of information and knowledge from all over the world, and so forth. Notwithstanding the continued efforts to develop these information systems, they still fail to provide essential support in the core creative activities of architectural designers. In order to understand why an appropriately effective support from information systems is so hard to realize, we started to look into the nature of design thinking and on how reasoning processes are at play in this design thinking. This investigation suggests that creative designing rests on a cyclic combination of abductive, deductive and inductive reasoning processes. Because traditional information systems typically target only one of these reasoning processes at a time, this could explain the limited applicability and usefulness of these systems. As research in information technology is increasingly targeting the combination of these reasoning modes, improvements may be within reach for design thinking support by information systems
FiLM: Visual Reasoning with a General Conditioning Layer
We introduce a general-purpose conditioning method for neural networks called
FiLM: Feature-wise Linear Modulation. FiLM layers influence neural network
computation via a simple, feature-wise affine transformation based on
conditioning information. We show that FiLM layers are highly effective for
visual reasoning - answering image-related questions which require a
multi-step, high-level process - a task which has proven difficult for standard
deep learning methods that do not explicitly model reasoning. Specifically, we
show on visual reasoning tasks that FiLM layers 1) halve state-of-the-art error
for the CLEVR benchmark, 2) modulate features in a coherent manner, 3) are
robust to ablations and architectural modifications, and 4) generalize well to
challenging, new data from few examples or even zero-shot.Comment: AAAI 2018. Code available at http://github.com/ethanjperez/film .
Extends arXiv:1707.0301
Architecture-Driven Semantic Analysis of Embedded Systems (Eds) Dagstuhl Seminar 12272
Architectural modeling of complex embedded systems is gaining prominence in recent years, both in academia and in industry. An architectural model represents components in a distributed system as boxes with well-defined interfaces, connections between ports on component interfaces, and specifies component properties that can be used in analytical reasoning about the model. Models are hierarchically organized, so that each box can contain another system inside, with its own set of boxes and connections between them.
The goal of Dagstuhl Seminar 12272 “Architecture-Driven Semantic Analysis of Embedded Systems” is to bring together researchers who are interested in defining precise semantics of an architecture description language and using it for building tools that generate analytical models from architectural ones, as well as generate code and configuration scripts for the system.
This report documents the program and the outcomes of the presentations and working groups held during the seminar
Style-Based architectural reconfigurations
We introduce Architectural Design Rewriting (ADR), an approach to the design of reconfigurable software architectures whose key features are: (i) rule-based approach (over graphs); (ii) hierarchical design; (iii) algebraic presentation; and (iv) inductively-defined reconfigurations. Architectures are modelled by graphs whose edges and nodes represent components and connection ports. Architectures are designed hierarchically by a set of edge replacement rules that fix the architectural style. Depending on their reading, productions allow: (i) top-down design by refinement, (ii) bottom-up typing of actual architectures, and (iii) well-formed composition of architectures. The key idea is to encode style proofs as terms and to exploit such information at run-time for guiding reconfigurations. The main advantages of ADR
are that: (i) instead of reasoning on flat architectures, ADR specifications provide a convenient hierarchical structure, by exploiting the architectural classes introduced by the style, (ii) complex reconfiguration schemes can be defined inductively, and (iii) style-preservation is guaranteed
Semantic reasoning for intelligent emergency response applications
Emergency response applications require the processing of large amounts of data, generated by a diverse set of sensors and devices, in order to provide for an accurate and concise view of the situation at hand. The adoption of semantic technologies allows for the definition of a formal domain model and intelligent data processing and reasoning on this model based on generated device and sensor measurements. This paper presents a novel approach to emergency response applications, such as fire fighting, integrating a formal semantic domain model into an event-based decision support system, which supports reasoning on this model. The developed model consists of several generic ontologies describing concepts and properties which can be applied to diverse context-aware applications. These are extended with emergency response specific ontologies. Additionally, inference on the model performed by a reasoning engine is dynamically synchronized with the rest of the architectural components. This allows to automatically trigger events based on predefined conditions. The proposed ontology and developed reasoning methodology is validated on two scenarios, i.e. (i) the construction of an emergency response incident and corresponding scenario and (ii) monitoring of the state of a fire fighter during an emergency response
Information system support in construction industry with semantic web technologies and/or autonomous reasoning agents
Information technology support is hard to find for the early design phases of the architectural design process. Many of the existing issues in such design decision support tools appear to be caused by a mismatch between the ways in which designers think and the ways in which information systems aim to give support. We therefore started an investigation of existing theories of design thinking, compared to the way in which design decision support systems provide information to the designer. We identify two main strategies towards information system support in the early design phase: (1) applications for making design try-outs, and (2) applications as autonomous reasoning agents. We outline preview implementations for both approaches and indicate to what extent these strategies can be used to improve information system support for the architectural designer
Principles of Knowledge Representation and Reasoning in the FRAPPE System
The purpose of this paper is to elucidate the following four important architectural principles of knowledge representation and reasoning with the example of an implemented system: limited reasoning, truth maintenance, hybrid architecture, and many sorted logic.MIT Artificial Intelligence Laborator
Discursive design thinking: the role of explicit knowledge in creative architectural design reasoning
The main hypothesis investigated in this paper is based upon the suggestion that the discursive reasoning in architecture supported by an explicit knowledge of spatial configurations can enhance both design productivity and the intelligibility of design solutions. The study consists of an examination of an architect’s performance while solving intuitively a well-defined problem followed by an analysis of the spatial structure of their design solutions. One group of architects will attempt to solve the design problem logically, rationalizing their design decisions by implementing their explicit knowledge of spatial configurations. The other group will use an implicit form of such knowledge arising from their architectural education to reason about their design acts. An integrated model of protocol analysis combining linkography and macroscopic coding is used to analyze the design processes. The resulting design outcomes will be evaluated quantitatively in terms of their spatial configurations. The analysis appears to show that an explicit knowledge of the rules of spatial configurations, as possessed by the first group of architects can partially enhance their function-driven judgment producing permeable and well-structured spaces. These findings are particularly significant as they imply that an explicit rather than an implicit knowledge of the fundamental rules that make a layout possible can lead to a considerable improvement in both the design process and product. This suggests that by externalizing th
Microservice Transition and its Granularity Problem: A Systematic Mapping Study
Microservices have gained wide recognition and acceptance in software
industries as an emerging architectural style for autonomic, scalable, and more
reliable computing. The transition to microservices has been highly motivated
by the need for better alignment of technical design decisions with improving
value potentials of architectures. Despite microservices' popularity, research
still lacks disciplined understanding of transition and consensus on the
principles and activities underlying "micro-ing" architectures. In this paper,
we report on a systematic mapping study that consolidates various views,
approaches and activities that commonly assist in the transition to
microservices. The study aims to provide a better understanding of the
transition; it also contributes a working definition of the transition and
technical activities underlying it. We term the transition and technical
activities leading to microservice architectures as microservitization. We then
shed light on a fundamental problem of microservitization: microservice
granularity and reasoning about its adaptation as first-class entities. This
study reviews state-of-the-art and -practice related to reasoning about
microservice granularity; it reviews modelling approaches, aspects considered,
guidelines and processes used to reason about microservice granularity. This
study identifies opportunities for future research and development related to
reasoning about microservice granularity.Comment: 36 pages including references, 6 figures, and 3 table
Machine-Checked Proofs For Realizability Checking Algorithms
Virtual integration techniques focus on building architectural models of
systems that can be analyzed early in the design cycle to try to lower cost,
reduce risk, and improve quality of complex embedded systems. Given appropriate
architectural descriptions, assume/guarantee contracts, and compositional
reasoning rules, these techniques can be used to prove important safety
properties about the architecture prior to system construction. For these
proofs to be meaningful, each leaf-level component contract must be realizable;
i.e., it is possible to construct a component such that for any input allowed
by the contract assumptions, there is some output value that the component can
produce that satisfies the contract guarantees. We have recently proposed (in
[1]) a contract-based realizability checking algorithm for assume/guarantee
contracts over infinite theories supported by SMT solvers such as linear
integer/real arithmetic and uninterpreted functions. In that work, we used an
SMT solver and an algorithm similar to k-induction to establish the
realizability of a contract, and justified our approach via a hand proof. Given
the central importance of realizability to our virtual integration approach, we
wanted additional confidence that our approach was sound. This paper describes
a complete formalization of the approach in the Coq proof and specification
language. During formalization, we found several small mistakes and missing
assumptions in our reasoning. Although these did not compromise the correctness
of the algorithm used in the checking tools, they point to the value of
machine-checked formalization. In addition, we believe this is the first
machine-checked formalization for a realizability algorithm.Comment: 14 pages, 1 figur
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