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Najjar, Amro
Publications (7 of 7) Show all publications
Mualla, Y., Najjar, A., Boissier, O., Galland, S., Tchappi Haman, I. & Vanet, R. (2019). A Cyber-Physical System for Semi-autonomous Oil & Gas Drilling Operations. In: 2019 Third IEEE International Conference on Robotic Computing (IRC): . Paper presented at The Third IEEE International Conference on Robotic Computing (IRC), Naples, Italy, February 25-27, 2019. (pp. 514-519). IEEE Computer Society
Open this publication in new window or tab >>A Cyber-Physical System for Semi-autonomous Oil & Gas Drilling Operations
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2019 (English)In: 2019 Third IEEE International Conference on Robotic Computing (IRC), IEEE Computer Society, 2019, p. 514-519Conference paper, Published paper (Refereed)
Abstract [en]

In Oil&Gas drilling operations and after reaching deep drilled depths, high temperature increases significantly enough to damage the down-hole drilling tools, and the existing mitigation process is insufficient. In this paper, we propose a Cyber-Physical System (CPS) where agents are used to represent the collaborating entities in Oil\&Gas fields both up-hole and down-hole. With the proposed CPS, down-hole tools respond to high temperature autonomously with a decentralized collective voting based on the tools' internal decision model while waiting for the cooling performed up-hole by the field engineer. This decision model, driven by the tools' specifications, aims to withstand high temperature. The proposed CPS is implemented using a multiagent simulation environment, and the results show that it mitigates high temperature properly with both the voting and the cooling mechanisms.

Place, publisher, year, edition, pages
IEEE Computer Society, 2019
Keywords
cyber-physical systems, multiagent systems, human-robot interaction, oil and gas drilling operations
National Category
Computer Systems
Identifiers
urn:nbn:se:umu:diva-157088 (URN)10.1109/IRC.2019.00107 (DOI)000465234000465234300098300098 ()978-1-5386-9245-5 (ISBN)
Conference
The Third IEEE International Conference on Robotic Computing (IRC), Naples, Italy, February 25-27, 2019.
Available from: 2019-03-08 Created: 2019-03-08 Last updated: 2019-06-28Bibliographically approved
Mualla, Y., Najjar, A., Galland, S., Nicolle, C., Tchappi, I. H., Yasar, A.-U. & Främling, K. (2019). Between the Megalopolis and the Deep Blue Sky: Challenges of Transport with UAVs in Future Smart Cities. In: AAMAS '19: PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS. Paper presented at 18th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), May 13-17, 2019, Montréal, Canada (pp. 1649-1653). ASSOC COMPUTING MACHINERY
Open this publication in new window or tab >>Between the Megalopolis and the Deep Blue Sky: Challenges of Transport with UAVs in Future Smart Cities
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2019 (English)In: AAMAS '19: PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS, ASSOC COMPUTING MACHINERY , 2019, p. 1649-1653Conference paper, Published paper (Refereed)
Abstract [en]

With the rapid increase of the world's urban population, the infrastructure of the constantly expanding metropolitan areas is undergoing an immense pressure. To meet the growing demands of sustainable urban environments and improve the quality of life for citizens, municipalities will increasingly rely on novel transport solutions. In particular, Unmanned Aerial Vehicles (UAVs) are expected to have a crucial role in the future smart cities thanks to their interesting features such as autonomy, flexibility, mobility, adaptive altitude, and small dimensions. However, densely populated megalopolises of the future are administrated by several municipals, governmental and civil society actors, where vivid economic activities involving a multitude of individual stakeholders take place. In such megalopolises, the use of agents for UAVs is gaining more interest especially in complex application scenarios where coordination and cooperation are necessary. This paper sketches a visionary view of the UAVs' role in the transport domain of future smart cities. Additionally, four challenging research directions are highlighted including problems related to autonomy, explainability, security and validation & verification of the UAVs behavior.

Place, publisher, year, edition, pages
ASSOC COMPUTING MACHINERY, 2019
Keywords
Multiagent Systems, Unmanned Aerial Vehicles, Intelligent Transport Systems, Smart Cities
National Category
Human Geography
Identifiers
urn:nbn:se:umu:diva-162359 (URN)000474345000190 ()978-1-4503-6309-9 (ISBN)
Conference
18th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), May 13-17, 2019, Montréal, Canada
Available from: 2019-09-10 Created: 2019-09-10 Last updated: 2019-09-10Bibliographically approved
Anjomshoae, S., Najjar, A., Calvaresi, D. & Främling, K. (2019). Explainable Agents and Robots: Results from a Systematic Literature Review. In: N. Agmon, M. E. Taylor, E. Elkind, M. Veloso (Ed.), Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems: . Paper presented at the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), Montreal, Canada, May 13–17, 2019 (pp. 1078-1088). International Foundation for Autonomous Agents and MultiAgent Systems
Open this publication in new window or tab >>Explainable Agents and Robots: Results from a Systematic Literature Review
2019 (English)In: Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems / [ed] N. Agmon, M. E. Taylor, E. Elkind, M. Veloso, International Foundation for Autonomous Agents and MultiAgent Systems , 2019, p. 1078-1088Conference paper, Published paper (Refereed)
Abstract [en]

Humans are increasingly relying on complex systems that heavily adopts Artificial Intelligence (AI) techniques. Such systems are employed in a growing number of domains, and making them explainable is an impelling priority. Recently, the domain of eXplainable Artificial Intelligence (XAI) emerged with the aims of fostering transparency and trustworthiness. Several reviews have been conducted. Nevertheless, most of them deal with data-driven XAI to overcome the opaqueness of black-box algorithms. Contributions addressing goal-driven XAI (e.g., explainable agency for robots and agents) are still missing. This paper aims at filling this gap, proposing a Systematic Literature Review. The main findings are (i) a considerable portion of the papers propose conceptual studies, or lack evaluations or tackle relatively simple scenarios; (ii) almost all of the studied papers deal with robots/agents explaining their behaviors to the human users, and very few works addressed inter-robot (inter-agent) explainability. Finally, (iii) while providing explanations to non-expert users has been outlined as a necessity, only a few works addressed the issues of personalization and context-awareness

Place, publisher, year, edition, pages
International Foundation for Autonomous Agents and MultiAgent Systems, 2019
Series
Proceedings, ISSN 2523-5699
Keywords
Explainable AI, goal-based XAI, autonomous agents, human-robot interaction
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:umu:diva-158024 (URN)978-1-4503-6309-9 (ISBN)
Conference
the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), Montreal, Canada, May 13–17, 2019
Available from: 2019-04-10 Created: 2019-04-10 Last updated: 2019-07-16Bibliographically approved
Anjomshoae, S., Främling, K. & Najjar, A. (2019). Explanations of black-box model predictions by contextual importance and utility. In: Davide Calvaresi, Amro Najjar, Michael Schumacher, Kary Främling (Ed.), Explainable, transparent autonomous agents and multi-agent systems: first international workshop, EXTRAAMAS 2019, Montreal, QC, Canada, May 13–14, 2019, revised selected papers (pp. 95-109). Springer
Open this publication in new window or tab >>Explanations of black-box model predictions by contextual importance and utility
2019 (English)In: Explainable, transparent autonomous agents and multi-agent systems: first international workshop, EXTRAAMAS 2019, Montreal, QC, Canada, May 13–14, 2019, revised selected papers / [ed] Davide Calvaresi, Amro Najjar, Michael Schumacher, Kary Främling, Springer, 2019, p. 95-109Chapter in book (Refereed)
Abstract [en]

The significant advances in autonomous systems together with an immensely wider application domain have increased the need for trustable intelligent systems. Explainable artificial intelligence is gaining considerable attention among researchers and developers to address this requirement. Although there is an increasing number of works on interpretable and trans- parent machine learning algorithms, they are mostly intended for the technical users. Explanations for the end-user have been neglected in many usable and practical applications. In this work, we present the Contextual Importance (CI) and Contextual Utility (CU) concepts to extract explanations that are easily understandable by experts as well as novice users. This method explains the prediction results without transforming the model into an interpretable one. We present an example of providing explanations for linear and non-linear models to demonstrate the generalizability of the method. CI and CU are numerical values that can be represented to the user in visuals and natural language form to justify actions and explain reasoning for individual instances, situations, and contexts. We show the utility of explanations in car selection example and Iris flower classification by presenting complete (i.e. the causes of an individual prediction) and contrastive explanation (i.e. contrasting instance against the instance of interest). The experimental results show the feasibility and validity of the provided explanation methods.

Place, publisher, year, edition, pages
Springer, 2019
Series
Lecture Notes in Computer Science (LNCS), ISSN 0302-9743, E-ISSN 1611-3349 ; 11763
Keywords
Explainable AI, Black-box models, Contextual importance, Contextual utility, Contrastive explanations
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:umu:diva-163549 (URN)10.1007/978-3-030-30391-4_6 (DOI)9783030303907 (ISBN)9783030303914 (ISBN)
Note

First International Workshop, EXTRAAMAS 2019, Montreal, QC, Canada, May 13–14, 2019

Available from: 2019-09-25 Created: 2019-09-25 Last updated: 2019-09-25Bibliographically approved
Kampik, T. & Najjar, A. (2019). Integrating Multi-agent Simulations into Enterprise Application Landscapes. In: De La Prieta F. et al. (Ed.), Highlights of Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection. PAAMS 2019. Paper presented at 17th International Conference on Practical Applications of Agents and Multi-Agent Systems, Ávila, Spain, 26th-28th June, 2019 (pp. 100-111).
Open this publication in new window or tab >>Integrating Multi-agent Simulations into Enterprise Application Landscapes
2019 (English)In: Highlights of Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection. PAAMS 2019 / [ed] De La Prieta F. et al., 2019, p. 100-111Conference paper, Published paper (Refereed)
Abstract [en]

To cope with increasingly complex business, political, and economic environments, agent-based simulations (ABS) have been proposed for modeling complex systems such as human societies, transport systems, and markets. ABS enable experts to assess the influence of exogenous parameters (e.g., climate changes or stock market prices), as well as the impact of policies and their long-term consequences. Despite some successes, the use of ABS is hindered by a set of interrelated factors. First, ABS are mainly created and used by researchers and experts in academia and specialized consulting firms. Second, the results of ABS are typically not automatically integrated into the corresponding business process. Instead, the integration is undertaken by human users who are responsible for adjusting the implemented policy to take into account the results of the ABS. These limitations are exacerbated when the results of the ABS affect multi-party agreements (e.g., contracts) since this requires all involved actors to agree on the validity of the simulation, on how and when to take its results into account, and on how to split the losses/gains caused by these changes. To address these challenges, this paper explores the integration of ABS into enterprise application landscapes. In particular, we present an architecture that integrates ABS into cross-organizational enterprise resource planning (ERP) processes. As part of this, we propose a multi-agent systems simulator for the Hyperledger blockchain and describe an example supply chain management scenario type to illustrate the approach.

Series
Communications in Computer and Information Science ; 1047
Keywords
Agent-Based Simulation, Business rules, Decision support systems, Business process management
National Category
Computer Engineering
Research subject
Computer Science
Identifiers
urn:nbn:se:umu:diva-161262 (URN)10.1007/978-3-030-24299-2_9 (DOI)978-3-030-24298-5 (ISBN)978-3-030-24299-2 (ISBN)
Conference
17th International Conference on Practical Applications of Agents and Multi-Agent Systems, Ávila, Spain, 26th-28th June, 2019
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)
Available from: 2019-07-01 Created: 2019-07-01 Last updated: 2019-07-03Bibliographically approved
Kampik, T. & Najjar, A. (2019). Technology-facilitated Societal Consensus. In: UMAP'19 Adjunct: Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization. Paper presented at UMAP 2019: The 27th ACM Conference on User Modelling, Adaptation and Personalization, Larnaca/Cyprus, June 9-12, 2019 (pp. 3-7). Larnaca, Cyprus: ACM Digital Library
Open this publication in new window or tab >>Technology-facilitated Societal Consensus
2019 (English)In: UMAP'19 Adjunct: Adjunct Publication of the 27th Conference on User Modeling, Adaptation and Personalization, Larnaca, Cyprus: ACM Digital Library, 2019, p. 3-7Conference paper, Published paper (Refereed)
Abstract [en]

The spread of radical opinions, facilitated by homophilic Internet communities (echo chambers), has become a threat to the stability of societies around the globe. The concept of choice architecture-the design of choice information for consumers with the goal of facilitating societally beneficial decisions-provides a promising (although not uncontroversial) general concept to address this problem. The choice architecture approach is reflected in recent proposals advocating for recommender systems that consider the societal impact of their recommendations and not only strive to optimize revenue streams. However, the precise nature of the goal state such systems should work towards remains an open question. In this paper, we suggest that this goal state can be defined by considering target opinion spread in a society on different topics of interest as a multivariate normal distribution; i.e., while there is a diversity of opinions, most people have similar opinions on most topics. We explain why this approach is promising, and list a set of cross-disciplinary research challenges that need to be solved to advance the idea.

Place, publisher, year, edition, pages
Larnaca, Cyprus: ACM Digital Library, 2019
Keywords
Choice architecture, Recommender systems, Persuasion
National Category
Human Computer Interaction
Research subject
human-computer interaction
Identifiers
urn:nbn:se:umu:diva-158477 (URN)10.1145/3314183.3323451 (DOI)978-1-4503-6711-0 (ISBN)
Conference
UMAP 2019: The 27th ACM Conference on User Modelling, Adaptation and Personalization, Larnaca/Cyprus, June 9-12, 2019
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)
Available from: 2019-04-28 Created: 2019-04-28 Last updated: 2019-07-17Bibliographically approved
Najjar, A., Picard, G. & Boissier, O. (2018). Négociation multi-agents résistante aux pics de charge pour améliorer l’acceptabilité des services d’un fournisseur SaaS ouvert. Revue d'intelligence artificielle: Revue des Sciences et Technologies de l'Information, 32(5-6), 603-625
Open this publication in new window or tab >>Négociation multi-agents résistante aux pics de charge pour améliorer l’acceptabilité des services d’un fournisseur SaaS ouvert
2018 (French)In: Revue d'intelligence artificielle: Revue des Sciences et Technologies de l'Information, ISSN 0992-499X, E-ISSN 1958-5748, Vol. 32, no 5-6, p. 603-625Article in journal (Refereed) Published
Abstract [fr]

Le taux d’acceptabilité d’un service et la satisfaction des utilisateurs deviennent des facteurs clés pour éviter le désabonnement des clients et sécuriser le succès de tout fournisseur de logiciel en tant que service (SaaS). Néanmoins, le fournisseur doit également répondre à des charges de travail fluctuantes et minimiser le coût de la location de ressources sur le cloud. Pour répondre à ces préoccupations contradictoires, la plupart des travaux existants effectuent unilatéralement la gestion des ressources par le fournisseur. Par conséquent, les préférences de l’utilisateur final et son acceptabilité subjective du service sont pour la plupart ignorées. Afin d’évaluer la satisfaction des utilisateurs et l’acceptabilité du service, des études récentes dans le domaine de la qualité de l’expérience (QoE) recommandent aux fournisseurs d’utiliser des quantiles et des percentiles pour évaluer précisément l’acceptabilité du service utilisateur. Dans cet article, nous proposons un mécanisme de négociation « one-to-many » élastique, résistant à la charge et adaptatif pour améliorer l’acceptabilité du service d’un fournisseur SaaS ouvert. Basé sur l’estimation du quantile du taux d’acceptabilité du service et sur un modèle appris de la stratégie de négociation utilisateur, ce mécanisme ajuste le processus de négociation du fournisseur afin de garantir le taux d’acceptabilité du service souhaité tout en respectant les limites budgétaires du fournisseur. Le mécanisme proposé est mis en œuvre et ses résultats expérimentaux sont examinés et analysés.

Abstract [en]

Service acceptability rate and user satisfaction are becoming key factors to avoid client churn and secure the success of any Software as a Service (SaaS) provider. Nevertheless, the provider must also accommodate fluctuating workloads and minimize the cost it pays to rent resources from the cloud. To address these contradicting concerns, most of existing works carry out resource management unilaterally by the provider. Consequently, end-user preferences and her subjective acceptability of the service are mostly ignored. In order to assess user satisfaction and service acceptability recent studies in the domain of Quality of Experience (QoE) recommend providers to use quantiles and percentile to gauge user service acceptability precisely. In this article we propose an elastic, load-spike proof, and adaptive one-to-many negotiation mechanism to improve the service acceptability of an open SaaS provider. Based on quantile estimation of service acceptability rate and a learned model of the user negotiation strategy, this mechanism adjusts the provider negotiation process in order to guarantee the desired service acceptability rate while meeting the budget limits of the provider and accommodating workload fluctuations. The proposed mechanism is implemented and its results are examined and analyzed.

Place, publisher, year, edition, pages
Lavoisier, 2018
Keywords
negotiation, adaptation, acceptability rate, SaaS, cloud computing, négociation, adaptation, taux d’acceptabilité, SaaS, cloud computing
National Category
Computer Systems
Identifiers
urn:nbn:se:umu:diva-154689 (URN)10.3166/ria.32.603-625 (DOI)
Available from: 2018-12-25 Created: 2018-12-25 Last updated: 2019-01-03Bibliographically approved
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