225,901 research outputs found
The DLV System for Knowledge Representation and Reasoning
This paper presents the DLV system, which is widely considered the
state-of-the-art implementation of disjunctive logic programming, and addresses
several aspects. As for problem solving, we provide a formal definition of its
kernel language, function-free disjunctive logic programs (also known as
disjunctive datalog), extended by weak constraints, which are a powerful tool
to express optimization problems. We then illustrate the usage of DLV as a tool
for knowledge representation and reasoning, describing a new declarative
programming methodology which allows one to encode complex problems (up to
-complete problems) in a declarative fashion. On the foundational
side, we provide a detailed analysis of the computational complexity of the
language of DLV, and by deriving new complexity results we chart a complete
picture of the complexity of this language and important fragments thereof.
Furthermore, we illustrate the general architecture of the DLV system which
has been influenced by these results. As for applications, we overview
application front-ends which have been developed on top of DLV to solve
specific knowledge representation tasks, and we briefly describe the main
international projects investigating the potential of the system for industrial
exploitation. Finally, we report about thorough experimentation and
benchmarking, which has been carried out to assess the efficiency of the
system. The experimental results confirm the solidity of DLV and highlight its
potential for emerging application areas like knowledge management and
information integration.Comment: 56 pages, 9 figures, 6 table
Designing and Deploying Online Field Experiments
Online experiments are widely used to compare specific design alternatives,
but they can also be used to produce generalizable knowledge and inform
strategic decision making. Doing so often requires sophisticated experimental
designs, iterative refinement, and careful logging and analysis. Few tools
exist that support these needs. We thus introduce a language for online field
experiments called PlanOut. PlanOut separates experimental design from
application code, allowing the experimenter to concisely describe experimental
designs, whether common "A/B tests" and factorial designs, or more complex
designs involving conditional logic or multiple experimental units. These
latter designs are often useful for understanding causal mechanisms involved in
user behaviors. We demonstrate how experiments from the literature can be
implemented in PlanOut, and describe two large field experiments conducted on
Facebook with PlanOut. For common scenarios in which experiments are run
iteratively and in parallel, we introduce a namespaced management system that
encourages sound experimental practice.Comment: Proceedings of the 23rd international conference on World wide web,
283-29
Complexity Theory, Adaptation, and Administrative Law
Recently, commentators have applied insights from complexity theory to legal analysis generally and to administrative law in particular. This Article focuses on one of the central problems that complexity. theory addresses, the importance and mechanisms of adaptation within complex systems. In Part I, the Article uses three features of complex adaptive systems-emergence from self-assembly, nonlinearity, and sensitivity to initial conditions-and explores the extent to which they may add value as a matter of positive analysis to the understanding of change within legal systems. In Part H, the Article focuses on three normative claims in public law scholarship that depend explicitly or implicitly on notions of adaptation: that states offer advantages over the federal government because experimentation can make them more adaptive, that federal agencies should themselves become more experimentalist using the tool of adaptive management, and that administrative agencies shou Id adopt collaborative mechanisms in policymaking. Using two analytic tools found in the complexity literature, the genetic algorithm and evolutionary game theory, the Article tests the extent to which these three normative claims are borne out
Sustaining entrepreneurial business: a complexity perspective on processes that produce emergent practice
This article examines the management practices in an entrepreneurial small firm which sustain the business. Using a longitudinal qualitative case study, four general processes are identified (experimentation, reflexivity, organising and sensing), that together provide a mechanism to sustain the enterprise. The analysis draws on concepts from entrepreneurship and complexity science. We suggest that an entrepreneur’s awareness of the role of these parallel processes will facilitate their approaches to sustaining and developing enterprises. We also suggest that these processes operate in parallel at multiple levels, including the self, the business and inter-firm networks. This finding contributes to a general theory of entrepreneurship. A number of areas for further research are discussed arising from this result
Carving out new business models in a small company through contextual ambidexterity: the case of a sustainable company
Business model innovation (BMI) and organizational ambidexterity have been pointed out as mechanisms for companies achieving sustainability. However, especially considering small and medium enterprises (SMEs), there is a lack of studies demonstrating how to combine these mechanisms. Tackling such a gap, this study seeks to understand how SMEs can ambidextrously manage BMI. Our aim is to provide a practical artifact, accessible to SMEs, to operationalize BMI through organizational ambidexterity. To this end, we conducted our study under the design science research to, first, build an artifact for operationalizing contextual ambidexterity for business model innovation. Then, we used an in-depth case study with a vegan fashion small e-commerce to evaluate the practical outcomes of the artifact. Our findings show that the company improves its business model while, at the same time, designs a new business model and monetizes it. Thus, our approach was able to take the first steps in the direction of operationalizing contextual ambidexterity for business model innovation in small and medium enterprises, democratizing the concept. We contribute to theory by connecting different literature strands and to practice by creating an artifact to assist managemen
CRIBs (Climate Relevant Innovation-system Builders): an effective way forward for international climate technology policy
National systems of innovation (NSIs) provide the context
within which all processes of technology development,
transfer and uptake occur - they refer to the network of actors (e.g. firms, universities, research institutes, government departments, NGOs) within which innovation occurs, and the strength and nature of the relationships between them. Nurturing NSIs in relation to climate technologies provides a powerful new focus for international policy with potential to underpin more sustained and widespread development and transfer of climate technologies. This working paper builds on
an invited presentation by one of the authors at a workshop on NSIs convened by the Technology Executive Committee (TEC) of the United Nations Framework Convention on Climate Change (UNFCCC). It identifies policy recommendations for consideration of the TEC. The intention is both to inform possible recommendations by the TEC to the UNFCCC Conference of the Parties (COP) and to highlight potential areas for future work that the TEC could undertake on this issue
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