| 1. |
- Deland, Mats, 1961-
(författare)
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Makten över marken
- 2021
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Ingår i: Arkitektur. - Stockholm : Arkitektur Förlag AB. - 0004-2021. ; :5, s. 64-70
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- This is an article about how the neo-liberalization of urban space has created a cityscape characterized by extreme segregation, gentrification and social inequality, in a very short period of time. It also traces how from the early Twentieth century an attempt was made to create a cityscape characterized by social integration and limitation of the power of market forces through the use of site leasehold rights (tomträtt/Erbbaurecht) and a large amount of municipal leaseholding. It follows this policy from 1904 to our days, and shows that the leasehold rights now have been integrated into the neo-liberal policy.
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| 2. |
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| 3. |
- Nolin, Catharina, 1962-
(författare)
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Sudda inte ut kvinnorna
- 2021
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Ingår i: Arkitektur. - 0004-2021. ; :2, s. 18-18
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Tidskriftsartikel (populärvet., debatt m.m.)
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| 4. |
- Sotoudeh Foumani, B., et al.
(författare)
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Multiple streams framework and logging policy change in the Hyrcanian forests of Iran
- 2021
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Ingår i: Australian Forestry. - : Taylor & Francis. - 0004-9158 .- 2325-6087. ; 84:4, s. 191-199
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Tidskriftsartikel (refereegranskat)abstract
- The 2017 logging ban in Iran’s Hyrcanian forests represents a considerable forest policy change,which was proposed following the development of other major policies to improve natural resourcemanagement. The aim of this paper is to explain the development of the logging ban policy usingKingdon’s multiple streams framework (MSF). Qualitative methods – interviewing and documentreview – were used for data collection and analysis. The problem, politics and policy streams areshown to be linked in framing the policy change. We investigate how participants in the developmentof the policy used interlinkages between the problem, politics and policy streams to develop theirproposals and how this simplified the change process. Despite some limitations, the MSF is helpful inexplaining and analysing outcomes of natural resource management policy development processes.
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| 5. |
- Manhaeve, Robin, et al.
(författare)
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Neural probabilistic logic programming in DeepProbLog
- 2021
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Ingår i: Artificial Intelligence. - : Elsevier. - 0004-3702 .- 1872-7921. ; 298
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Tidskriftsartikel (refereegranskat)abstract
- We introduce DeepProbLog, a neural probabilistic logic programming language that incorporates deep learning by means of neural predicates. We show how existing inference and learning techniques of the underlying probabilistic logic programming language ProbLog can be adapted for the new language. We theoretically and experimentally demonstrate that DeepProbLog supports (i) both symbolic and subsymbolic representations and inference, (ii) program induction, (iii) probabilistic (logic) programming, and (iv)(deep) learning from examples. To the best of our knowledge, this work is the first to propose a framework where general-purpose neural networks and expressive probabilistic-logical modeling and reasoning are integrated in a way that exploits the full expressiveness and strengths of both worlds and can be trained end-to-end based on examples. (C) 2021 Elsevier B.V. All rights reserved.
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| 6. |
- Winikoff, Michael, et al.
(författare)
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Why bad coffee? Explaining BDI agent behaviour with valuings
- 2021
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Ingår i: Artificial Intelligence. - Amsterdam : Elsevier. - 0004-3702 .- 1872-7921. ; 300
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Tidskriftsartikel (refereegranskat)abstract
- An important issue in deploying an autonomous system is how to enable human users and stakeholders to develop an appropriate level of trust in the system. It has been argued that a crucial mechanism to enable appropriate trust is the ability of a system to explain its behaviour. Obviously, such explanations need to be comprehensible to humans. Due to the perceived similarity in functioning between humans and autonomous systems, we argue that it makes sense to build on the results of extensive research in social sciences that explores how humans explain their behaviour. Using similar concepts for explanation is argued to help with comprehensibility, since the concepts are familiar. Following work in the social sciences, we propose the use of a folk-psychological model that utilises beliefs, desires, and “valuings”. We propose a formal framework for constructing explanations of the behaviour of an autonomous system, present an (implemented) algorithm for giving explanations, and present evaluation results. © 2021 Elsevier B.V.
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| 7. |
- Ghalme, Ganesh, et al.
(författare)
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Ballooning multi-armed bandits
- 2021
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Ingår i: Artificial Intelligence. - : Elsevier BV. - 0004-3702. ; 296
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we introduce ballooning multi-armed bandits (BL-MAB), a novel extension of the classical stochastic MAB model. In the BL-MAB model, the set of available arms grows (or balloons) over time. In contrast to the classical MAB setting where the regret is computed with respect to the best arm overall, the regret in a BL-MAB setting is computed with respect to the best available arm at each time. We first observe that the existing stochastic MAB algorithms result in linear regret for the BL-MAB model. We prove that, if the best arm is equally likely to arrive at any time instant, a sub-linear regret cannot be achieved. Next, we show that if the best arm is more likely to arrive in the early rounds, one can achieve sub-linear regret. Our proposed algorithm determines (1) the fraction of the time horizon for which the newly arriving arms should be explored and (2) the sequence of arm pulls in the exploitation phase from among the explored arms. Making reasonable assumptions on the arrival distribution of the best arm in terms of the thinness of the distribution's tail, we prove that the proposed algorithm achieves sub-linear instance-independent regret. We further quantify explicit dependence of regret on the arrival distribution parameters. We reinforce our theoretical findings with extensive simulation results. We conclude by showing that our algorithm would achieve sub-linear regret even if (a) the distributional parameters are not exactly known, but are obtained using a reasonable learning mechanism or (b) the best arm is not more likely to arrive early, but a large fraction of arms is likely to arrive relatively early.
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| 8. |
- Jonsson, Peter, 1969-, et al.
(författare)
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Acyclic orders, partition schemes and CSPs : Unified hardness proofs and improved algorithms
- 2021
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Ingår i: Artificial Intelligence. - : Elsevier. - 0004-3702 .- 1872-7921. ; 296
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Tidskriftsartikel (refereegranskat)abstract
- Many computational problems arising in, for instance, artificial intelligence can be realized as infinite-domain constraint satisfaction problems (CSPs) based on partition schemes: a set of pairwise disjoint binary relations (containing the equality relation) whose union spans the underlying domain and which is closed under converse. We first consider partition schemes that contain an acyclic order and where the constraint language contains all unions of the basic relations; such CSPs are frequently occurring in e.g. temporal and spatial reasoning. We identify properties of such orders which, when combined, are sufficient to establish NP-hardness of the CSP and strong lower bounds under the exponential-time hypothesis, even for degree-bounded problems. This result explains, in a uniform way, many existing hardness results from the literature, and shows that it is impossible to obtain subexponential time algorithms unless the exponential-time hypothesis fails. However, some of these problems (including several important temporal problems), despite likely not being solvable in subexponential time, admit non-trivial improved exponential-time algorithm, and we present a novel improved algorithm for RCC-8 and related formalisms.
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| 9. |
- Riveiro, Maria, 1978-, et al.
(författare)
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“That's (not) the output I expected!” On the role of end user expectations in creating explanations of AI systems
- 2021
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Ingår i: Artificial Intelligence. - : Elsevier. - 0004-3702 .- 1872-7921. ; 298
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Tidskriftsartikel (refereegranskat)abstract
- Research in the social sciences has shown that expectations are an important factor in explanations as used between humans: rather than explaining the cause of an event per se, the explainer will often address another event that did not occur but that the explainee might have expected. For AI-powered systems, this finding suggests that explanation-generating systems may need to identify such end user expectations. In general, this is a challenging task, not the least because users often keep them implicit; there is thus a need to investigate the importance of such an ability.In this paper, we report an empirical study with 181 participants who were shown outputs from a text classifier system along with an explanation of why the system chose a particular class for each text. Explanations were both factual, explaining why the system produced a certain output or counterfactual, explaining why the system produced one output instead of another. Our main hypothesis was explanations should align with end user expectations; that is, a factual explanation should be given when the system's output is in line with end user expectations, and a counterfactual explanation when it is not.We find that factual explanations are indeed appropriate when expectations and output match. When they do not, neither factual nor counterfactual explanations appear appropriate, although we do find indications that our counterfactual explanations contained at least some necessary elements. Overall, this suggests that it is important for systems that create explanations of AI systems to infer what outputs the end user expected so that factual explanations can be generated at the appropriate moments. At the same time, this information is, by itself, not sufficient to also create appropriate explanations when the output and user expectations do not match. This is somewhat surprising given investigations of explanations in the social sciences, and will need more scrutiny in future studies.
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| 10. |
- Suchan, Jakob, et al.
(författare)
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Commonsense Visual Sensemaking for Autonomous Driving : On Generalised Neurosymbolic Online Abduction Integrating Vision and Semantics
- 2021
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Ingår i: Artificial Intelligence. - : Elsevier. - 0004-3702 .- 1872-7921. ; 299
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Tidskriftsartikel (refereegranskat)abstract
- We demonstrate the need and potential of systematically integrated vision and semantics solutions for visual sensemaking in the backdrop of autonomous driving. A general neurosymbolic method for online visual sensemaking using answer set programming (ASP) is systematically formalised and fully implemented. The method integrates state of the art in visual computing, and is developed as a modular framework that is generally usable within hybrid architectures for realtime perception and control. We evaluate and demonstrate with community established benchmarks KITTIMOD, MOT-2017, and MOT-2020. As use-case, we focus on the significance of human-centred visual sensemaking —e.g., involving semantic representation and explainability, question-answering, commonsense interpolation— in safety-critical autonomous driving situations. The developed neurosymbolic framework is domain-independent, with the case of autonomous driving designed to serve as an exemplar for online visual sensemaking in diverse cognitive interaction settings in the backdrop of select human-centred AI technology design considerations.
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