| 1. |
- Dignum, Frank, et al.
(författare)
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Analysing the Combined Health, Social and Economic Impacts of the Corovanvirus Pandemic Using Agent-Based Social Simulation
- 2020
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Ingår i: Minds and Machines. - : Springer. - 0924-6495 .- 1572-8641. ; 30:2, s. 177-194
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Tidskriftsartikel (refereegranskat)abstract
- During the COVID-19 crisis there have been many difficult decisions governments and other decision makers had to make. E.g. do we go for a total lock down or keep schools open? How many people and which people should be tested? Although there are many good models from e.g. epidemiologists on the spread of the virus under certain conditions, these models do not directly translate into the interventions that can be taken by government. Neither can these models contribute to understand the economic and/or social consequences of the interventions. However, effective and sustainable solutions need to take into account this combination of factors. In this paper, we propose an agent-based social simulation tool, ASSOCC, that supports decision makers understand possible consequences of policy interventions, but exploring the combined social, health and economic consequences of these interventions.
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| 2. |
- Frank, Dignum, et al.
(författare)
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Introduction
- 2021
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Ingår i: Social Simulation for a Crisis. - Cham : Springer. - 9783030763961 - 9783030763978 ; , s. 3-13
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- The introduction of this book sets the stage of performing social simulations in a crisis. The contents of the book are based on the experience of creating a large scale and complex social simulation for the Covid-19 crisis. However, the contents are reaching much further than just this experience. We will show the general contribution that social simulations based on fundamental social-psychological principles can have in times of crises. In times of big societal changes due to a pandemic or other disaster, these simulations can give handles to support decision makers in their difficult task to act in a very short time with many uncertainties. Besides giving our results, we also will indicate why the results are trustworthy and interesting. Finally we also look what challenges should be picked up to convert the successful project into a sustainable research area.
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| 3. |
- Gutsche, Linda, et al.
(författare)
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The value of knowledge : joining reward and epistemic certainty optimisation for anxiety-sensitive planning
- 2024
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Ingår i: Autonomous agents and multiagent systems. - : Springer. - 9783031562549 - 9783031562556 ; , s. 30-42
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Bokkapitel (refereegranskat)abstract
- Anxiety is one of the most basic emotional states and also the most common disorder. AI agents however are typically focused on maximising performance, concentrating on expected values and disregarding the degree of exposure to uncertainty. This paper introduces a formalism derived from Partially Observable Markov Decision Processes (POMDPs) to give the first model based on cognitive psychology of the anxiety induced by epistemic uncertainty (i.e. the lack of precision of knowledge about the current state of the world). An algorithm to generate policies balancing reward maximisation and anxiety reduction is given. It is then used on a classical example to demonstrate how this can lead in some cases to a dramatic reduction of epistemic uncertainty for nearly no cost and thus a more human-friendly reward optimisation. The empirical validation shows results reminiscent of behaviours that cognitive psychology identifies as coping mechanisms to anxiety.
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| 4. |
- Horned, Arvid, et al.
(författare)
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From threatening pasts to hopeful futures : a review of agent-based models of anxiety
- 2023
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Ingår i: Advances in social simulation. - : Springer Nature. - 9783031349195 - 9783031349225 - 9783031349201 ; , s. 139-152
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Konferensbidrag (refereegranskat)abstract
- Despite being understated, anxiety is a critical factor affecting all levels of society, directly impacting individual decisions and with well-identified ramifications on social play, social constructs, and collective outcomes, as well as being a significant direct social toll tied to yearly trillion-USD social cost. Through a systematic literature review of social simulation research featuring models of anxiety, this paper frames the state of the art on anxiety modelling, and identifies trends and patterns in bibliographic indicators, aspects of anxiety that are modelled, how they are modelled, and their purpose and integration within agent based models. Based on these findings, this paper proposes a way forward as to structure the field as to enable the social simulation community as a whole to cover this critical aspect.
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| 5. |
- Horned, Arvid, et al.
(författare)
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Models of anxiety for agent deliberation : the benefits of anxiety-sensitive agents blue sky ideas track
- 2023
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Ingår i: Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023). - : International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). ; , s. 1761-1767
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Konferensbidrag (refereegranskat)abstract
- Anxiety is one of the most critical sources of harm to psychological wellbeing, tied to an array of issues, from discomfort and maladaptive coping to severe pathological disorders -making of anxiety one of the largest economic and social healthcare expenses. AI systems are not neutral to the exposure of individuals and societies to anxiety, and the current emphasis on performance-optimization of current AI systems arguably sets a pathway for a systemic rise of anxiety. As a response to this trend, towards further increasing the human-centeredness of existing applications, this paper is dedicated to depicting the landscape of open challenges, high-impact applications, and promising solutions for designing anxiety-sensitive agents. This paper first circumvents the key components of anxiety through a summary of the extensive psychology literature on anxiety; then shows the feasibility of building agent-based models by putting forward an example of a logical model of anxiety; and last, examines current research fields through the lens of anxiety, highlighting categories of prospective applications and techniques which stand to benefit from anxiety-sensitive agents.
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| 6. |
- Javed, Rana Tallal, et al.
(författare)
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Get out of the BAG! Silos in AI ethics education : unsupervised topic modeling analysis of global AI curricula (extended abstract)
- 2023
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Ingår i: Proceedings of the thirty-second international joint conference on artificial intelligence. - : International Joint Conferences on Artificial Intelligence. - 9781956792034 ; , s. 6905-6909
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Konferensbidrag (refereegranskat)abstract
- This study explores the topics and trends of teaching AI ethics in higher education, using Latent Dirichlet Allocation as the analysis tool. The analyses included 166 courses from 105 universities around the world. Building on the uncovered patterns, we distil a model of current pedagogical practice, the BAG model (Build, Assess, and Govern), that combines cognitive levels, course content, and disciplines. The study critically assesses the implications of this teaching paradigm and challenges practitioners to reflect on their practices and move beyond stereotypes and biases.
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| 7. |
- Javed, Rana Tallal, et al.
(författare)
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Get out of the BAG! Silos in AI Ethics Education: Unsupervised Topic Modeling Analysis of Global AI Curricula
- 2022
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Ingår i: Journal of Artificial Intelligence Research. - : AI Access Foundation. - 1076-9757 .- 1943-5037. ; 73, s. 933-965
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Tidskriftsartikel (refereegranskat)abstract
- The domain of Artificial Intelligence (AI) ethics is not new, with discussions going back at least 40 years. Teaching the principles and requirements of ethical AI to students is considered an essential part of this domain, with an increasing number of technical AI courses taught at several higher-education institutions around the globe including content related to ethics. By using Latent Dirichlet Allocation (LDA), a generative probabilistic topic model, this study uncovers topics in teaching ethics in AI courses and their trends related to where the courses are taught, by whom, and at what level of cognitive complexity and specificity according to Bloom’s taxonomy. In this exploratory study based on unsupervised machine learning, we analyzed a total of 166 courses: 116 from North American universities, 11 from Asia, 36 from Europe, and 10 from other regions. Based on this analysis, we were able to synthesize a model of teaching approaches, which we call BAG (Build, Assess, and Govern), that combines specific cognitive levels, course content topics, and disciplines affiliated with the department(s) in charge of the course. We critically assess the implications of this teaching paradigm and provide suggestions about how to move away from these practices. We challenge teaching practitioners and program coordinators to reflect on their usual procedures so that they may expand their methodology beyond the confines of stereotypical thought and traditional biases regarding what disciplines should teach and how.
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| 8. |
- Jensen, Maarten, et al.
(författare)
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Agile Social Simulations for Resilience
- 2021
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Ingår i: Social Simulation for a Crisis. - Cham : Springer. - 9783030763961 - 9783030763978 ; , s. 37-408
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- In previous chapters we have described the results and analysis of social simulations for crisis situations based on the experiences of the ASSOCC framework. Whereas we managed to build an implementation in a very short time, based on many years of fundamental research, such an implementation is inherently limited due to the many tasks and challenges that are to be dealt within high time pressure (e.g. keeping up with the many emerging public concerns and specific stakeholder issues with relatively unstable theoretical background while dealing with scaling up technical challenges). This chapter proposes and discusses what can be prepared for future crises, from fundamental conceptual building blocks, to decision components, and technical implementations. Building upon the experience of what we missed and had to create or deal with(out) during the crisis, this chapter is dedicated to point how, as a community, we can be ready to adaptively respond to future crises.
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| 9. |
- Jensen, Maarten, et al.
(författare)
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Deployment and Effects of an App for Tracking and Tracing Contacts during the COVID-19 Crisis
- 2021
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Ingår i: Social Simulation for a Crisis. - Cham : Springer. - 9783030763961 - 9783030763978 ; , s. 167-188
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- The general idea of tracking and tracing apps is that they track the contacts of users so that in case a user tests positive for COVID-19, all the other users that she has been in contact with get a warning signal that they have potentially been in contact with the COVID-19 virus. This is, to quarantine potential carriers of the virus even before they show symptoms. We set up a scenario in which we test the effects the introduction of such an app has on the dynamics of infection with varying amounts of app users. Running the experiments resulted in a slightly lower peak of infections for higher app usages and the total amount of infected individuals over the course of the whole run decreased not more than 10% in any case. The app seems mainly effective in decreasing contacts and infections in public spaces (except hospitals) while increasing the contacts and infections at home.
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| 10. |
- Jensen, Maarten, et al.
(författare)
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Dynamic context-sensitive deliberation
- 2024
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Ingår i: Multi-Agent-Based simulation XXIV. - : Springer Nature. - 9783031610332 - 9783031610349 ; , s. 112-126
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Bokkapitel (refereegranskat)abstract
- Truly realistic models for policy making require multiple aspects of life, realistic social behaviour and the ability to simulate millions of agents. Current state of the art Agent-based models only achieve two of these requirements. Models that prioritise realistic social behaviour are not easily scalable because the complex deliberation takes into account all information available at each time step for each agent. Our framework uses context to considerably narrow down the information that has to be considered. A key property of the framework is that it can dynamically slide between fast deliberation and complex deliberation. Context is expanded based on necessity. We introduce the elements of the framework, describe the architecture and show a proof-of-concept implementation. We give first steps towards validation using this implementation.
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