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Frasheri, Mirgita
Publications (10 of 12) Show all publications
Miloradović, B., Frasheri, M., Curuklu, B., Ekström, M. & Papadopoulos, A. (2019). TAMER: Task Allocation in Multi-robot Systems Through an Entity-Relationship Model. In: PRIMA 2019: Principles and Practice of Multi-Agent Systems. Paper presented at The 22nd International Conference on Principles and Practice of Multi-Agent Systems PRIMA'19, 28 Oct 2019, Turin, Italy (pp. 478-486).
Open this publication in new window or tab >>TAMER: Task Allocation in Multi-robot Systems Through an Entity-Relationship Model
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2019 (English)In: PRIMA 2019: Principles and Practice of Multi-Agent Systems, 2019, p. 478-486Conference paper, Published paper (Refereed)
Abstract [en]

Multi-robot task allocation (MRTA) problems have been studied extensively in the past decades. As a result, several classifications have been proposed in the literature targeting different aspects of MRTA, with often a few commonalities between them. The goal of this paper is twofold. First, a comprehensive overview of early work on existing MRTA taxonomies is provided, focusing on their differences and similarities. Second, the MRTA problem is modelled using an Entity-Relationship (ER) conceptual formalism to provide a structured representation of the most relevant aspects, including the ones proposed within previous taxonomies. Such representation has the advantage of (i) representing MRTA problems in a systematic way, (ii) providing a formalism that can be easily transformed into a software infrastructure, and (iii) setting the baseline for the definition of knowledge bases, that can be used for automated reasoning in MRTA problems.

National Category
Engineering and Technology Computer Systems
Identifiers
urn:nbn:se:mdh:diva-46316 (URN)10.1007/978-3-030-33792-6_32 (DOI)978-3-030-33791-9 (ISBN)
Conference
The 22nd International Conference on Principles and Practice of Multi-Agent Systems PRIMA'19, 28 Oct 2019, Turin, Italy
Projects
DPAC - Dependable Platforms for Autonomous systems and ControlUnicorn -Sustainable, peaceful and efficient robotic refuse handlingAggregate Farming in the Cloud
Available from: 2019-12-12 Created: 2019-12-12 Last updated: 2019-12-12Bibliographically approved
Enoiu, E. P. & Frasheri, M. (2019). Test agents: The next generation of test cases. In: Proceedings - 2019 IEEE 12th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2019: . Paper presented at 12th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2019; Xi'an; China; 22 April 2019 through 27 April 2019 (pp. 305-308). Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Test agents: The next generation of test cases
2019 (English)In: Proceedings - 2019 IEEE 12th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2019, Institute of Electrical and Electronics Engineers Inc. , 2019, p. 305-308Conference paper, Published paper (Refereed)
Abstract [en]

Growth of software size, lack of resources to perform regression testing, and failure to detect bugs faster have seen increased reliance on continuous integration and test automation. Even with greater hardware and software resources dedicated to test automation, software testing is faced with enormous challenges, resulting in increased dependence on centralized and complex mechanisms for automated test case selection as part of continuous integration. These mechanisms are currently using static entities called test cases that are concretely realized as executable scripts. Our key vision is to provide test cases with more reasoning, adaptive behavior and learning capabilities by using the concepts of software agents. We refer to such test cases as test agents. The model that underlie a test agent is capable of flexible and autonomous actions in order to meet overall testing objectives. Our goal is to increase the decentralization of regression testing by letting test agents to know for themselves when they should be executing, how they should update their purpose, and when they should interact with each other. In this paper, we envision test agents that display such adaptive autonomous behavior. Existing and emerging developments and challenges regarding the use of test agents are explored - in particular, new research that seeks to use adaptive autonomous agents in software testing. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2019
Keywords
Adaptive, Agent, Autonomous, Regression, Software testing, Test automation, Test design
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:mdh:diva-44914 (URN)10.1109/ICSTW.2019.00070 (DOI)000477742600046 ()2-s2.0-85068394558 (Scopus ID)9781728108889 (ISBN)
Conference
12th IEEE International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2019; Xi'an; China; 22 April 2019 through 27 April 2019
Available from: 2019-07-18 Created: 2019-07-18 Last updated: 2019-08-15Bibliographically approved
Frasheri, M., Curuklu, B., Ekström, M. & Papadopoulos, A. (2018). Adaptive Autonomy in a Search and Rescue Scenario. In: International Conference on Self-Adaptive and Self-Organizing Systems, SASO, Volume 2018-September, 15 January 2019: . Paper presented at 12th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2018; Trento; Italy; 3 September 2018 through 7 September 2018 (pp. 150-155).
Open this publication in new window or tab >>Adaptive Autonomy in a Search and Rescue Scenario
2018 (English)In: International Conference on Self-Adaptive and Self-Organizing Systems, SASO, Volume 2018-September, 15 January 2019, 2018, p. 150-155Conference paper, Published paper (Refereed)
Abstract [en]

Adaptive autonomy plays a major role in the design of multi-robots and multi-agent systems, where the need of collaboration for achieving a common goal is of primary importance. In particular, adaptation becomes necessary to deal with dynamic environments, and scarce available resources. In this paper, a mathematical framework for modelling the agents' willingness to interact and collaborate, and a dynamic adaptation strategy for controlling the agents' behavior, which accounts for factors such as progress toward a goal and available resources for completing a task among others, are proposed. The performance of the proposed strategy is evaluated through a fire rescue scenario, where a team of simulated mobile robots need to extinguish all the detected fires and save the individuals at risk, while having limited resources. The simulations are implemented as a ROS-based multi agent system, and results show that the proposed adaptation strategy provides a more stable performance than a static collaboration policy. 

National Category
Engineering and Technology Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:mdh:diva-40254 (URN)10.1109/SASO.2018.00026 (DOI)000459885200016 ()2-s2.0-85061910844 (Scopus ID)9781538651728 (ISBN)
Conference
12th IEEE International Conference on Self-Adaptive and Self-Organizing Systems, SASO 2018; Trento; Italy; 3 September 2018 through 7 September 2018
Available from: 2018-07-18 Created: 2018-07-18 Last updated: 2019-03-14Bibliographically approved
Frasheri, M., Curuklu, B. & Ekström, M. (2018). Analysis of perceived helpfulness in adaptive autonomous agent populations. In: Transactions on Computational Collective Intelligence XXVIII: . Paper presented at International Conference on Agents and Artificial Intelligence, ICAART 2016 and 2017 (pp. 221-252). Springer Verlag, 10780
Open this publication in new window or tab >>Analysis of perceived helpfulness in adaptive autonomous agent populations
2018 (English)In: Transactions on Computational Collective Intelligence XXVIII, Springer Verlag , 2018, Vol. 10780, p. 221-252Conference paper, Published paper (Refereed)
Abstract [en]

Adaptive autonomy allows agents to change their autonomy levels based on circumstances, e.g. when they decide to rely upon one another for completing tasks. In this paper, two configurations of agent models for adaptive autonomy are discussed. In the former configuration, the adaptive autonomous behavior is modeled through the willingness of an agent to assist others in the population. An agent that completes a high number of tasks, with respect to a predefined threshold, increases its willingness, and vice-versa. Results show that, agents complete more tasks when they are willing to give help, however the need for such help needs to be low. Agents configured to be helpful will perform well among alike agents. The second configuration extends the first by adding the willingness to ask for help. Furthermore, the perceived helpfulness of the population and of the agent asking for help are used as input in the calculation of the willingness to give help. Simulations were run for three different scenarios. (i) A helpful agent which operates among an unhelpful population, (ii) an unhelpful agent which operates in a helpful populations, and (iii) a population split in half between helpful and unhelpful agents. Results for all scenarios show that, by using such trait of the population in the calculation of willingness and given enough interactions, helpful agents can control the degree of exploitation by unhelpful agents. © Springer International Publishing AG, part of Springer Nature 2018.

Place, publisher, year, edition, pages
Springer Verlag, 2018
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 10780
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-39195 (URN)10.1007/978-3-319-78301-7_10 (DOI)2-s2.0-85046355290 (Scopus ID)978-3-319-78301-7 (ISBN)
Conference
International Conference on Agents and Artificial Intelligence, ICAART 2016 and 2017
Note

This twenty-eight issue is a special issue with 11 selected papers from the International Conference on Agents and Artificial Intelligence, ICAART 2016 and 2017 editions.

Available from: 2018-05-11 Created: 2018-05-11 Last updated: 2018-07-18Bibliographically approved
Frasheri, M. (2018). Collaborative adaptive autonomous agents. In: Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS: . Paper presented at 17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018, 10 July 2018 through 15 July 2018 (pp. 1740-1742). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 3
Open this publication in new window or tab >>Collaborative adaptive autonomous agents
2018 (English)In: Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS) , 2018, Vol. 3, p. 1740-1742Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2018
Keywords
Adaptive autonomy, Collaborative agents, Multi-agent systems
National Category
Embedded Systems
Identifiers
urn:nbn:se:mdh:diva-41232 (URN)000468231300210 ()2-s2.0-85054726600 (Scopus ID)9781510868083 (ISBN)
Conference
17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018, 10 July 2018 through 15 July 2018
Available from: 2018-10-26 Created: 2018-10-26 Last updated: 2019-06-05Bibliographically approved
Frasheri, M. (2018). Collaborative Adaptive Autonomous Agents. (Licentiate dissertation). Mälardalen University Press
Open this publication in new window or tab >>Collaborative Adaptive Autonomous Agents
2018 (English)Licentiate thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Mälardalen University Press, 2018
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 271
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:mdh:diva-40255 (URN)978-91-7485-399-5 (ISBN)
Presentation
2018-09-14, Gamma, Mälardalens högskola, Västerås, 09:15 (English)
Opponent
Supervisors
Available from: 2018-07-19 Created: 2018-07-18 Last updated: 2019-10-01Bibliographically approved
Frasheri, M., Curuklu, B. & Ekström, M. (2018). Comparison Between Static and Dynamic Willingness to Interact in Adaptive Autonomous Agents. In: Proceedings of the 10th International Conference on Agents and Artificial Intelligence: . Paper presented at 10th International Conference on Agents and Artificial Intelligence ICAART'18, 16 Jan 2018, Funchal, Madeira, Portugal (pp. 258-267). , 1
Open this publication in new window or tab >>Comparison Between Static and Dynamic Willingness to Interact in Adaptive Autonomous Agents
2018 (English)In: Proceedings of the 10th International Conference on Agents and Artificial Intelligence, 2018, Vol. 1, p. 258-267Conference paper, Published paper (Refereed)
Abstract [en]

Adaptive autonomy (AA) is a behavior that allows agents to change their autonomy levels by reasoning on their circumstances. Previous work has modeled AA through the willingness to interact, composed of willingness to ask and give assistance. The aim of this paper is to investigate, through computer simulations, the behavior of agents given the proposed computational model with respect to different initial configurations, and level of dependencies between agents. Dependency refers to the need for help that one agent has. Such need can be fulfilled by deciding to depend on other agents. Results show that, firstly, agents whose willingness to interact changes during run-time perform better compared to those with static willingness parameters, i.e. willingness with fixed values. Secondly, two strategies for updating the willingness are compared, (i) the same fixed value is updated on each interaction, (ii) update is done on the previous calculated value. The maximum number of completed tasks which need assistance is achieved for (i), given specific initial configurations.

Keywords
Adaptive Autonomy, Multi-agent Systems, Collaborative Agents
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-38963 (URN)10.5220/0006648002580267 (DOI)2-s2.0-85047721508 (Scopus ID)978-989-758-275-2 (ISBN)
Conference
10th International Conference on Agents and Artificial Intelligence ICAART'18, 16 Jan 2018, Funchal, Madeira, Portugal
Available from: 2018-05-08 Created: 2018-05-08 Last updated: 2018-07-18Bibliographically approved
Enoiu, E. P. & Frasheri, M. (2018). Test Agents: Adaptive, Autonomous and Intelligent Test Cases.
Open this publication in new window or tab >>Test Agents: Adaptive, Autonomous and Intelligent Test Cases
2018 (English)Manuscript (preprint) (Other academic)
Abstract [en]

Growth of software size, lack of resources to perform regression testing, and failure to detect bugs faster have seen increased reliance on continuous integration and test automation. Even with greater hardware and software resources dedicated to test automation, software testing is faced with enormous challenges, resulting in increased dependence on complex mechanisms for automated test case selection and prioritisation as part of a continuous integration framework. These mechanisms are currently using simple entities called test cases that are concretely realised as executable scripts. Our key idea is to provide test cases with more reasoning, adaptive behaviour and learning capabilities by using the concepts of intelligent software agents. We refer to such test cases as test agents. The model that underlie a test agent is capable of flexible and autonomous actions in order to meet overall testing objectives. Our goal is to increase the decentralisation of regression testing by letting test agents to know for themselves when they should be executing, how they should update their purpose, and when they should interact with each other. In this paper, we envision software test agents that display such adaptive autonomous behaviour. Emerging developments and challenges regarding the use of test agents are explored-in particular, new research that seeks to use adaptive autonomous agents in software testing.

National Category
Engineering and Technology Computer Systems
Identifiers
urn:nbn:se:mdh:diva-41696 (URN)
Projects
MegaMaRt2 - Megamodelling at Runtime (ECSEL/Vinnova)Software Center: Aspects of Automated Testing
Available from: 2018-12-18 Created: 2018-12-18 Last updated: 2018-12-18Bibliographically approved
Al-Rawi, M., Elmgren, F., Frasheri, M., Curuklu, B., Yuan, X., Martínez, J.-F., . . . Pinto, M. (2017). Algorithms for the Detection of First Bottom Returns and Objects in the Water Column in Side-Scan Sonar Images. In: OCEANS '17 A Vision for our Marine Future OCEANS '17: . Paper presented at OCEANS '17 A Vision for our Marine Future OCEANS '17, 19 Jun 2017, Aberdeen, United Kingdom. Aberdeen, United Kingdom
Open this publication in new window or tab >>Algorithms for the Detection of First Bottom Returns and Objects in the Water Column in Side-Scan Sonar Images
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2017 (English)In: OCEANS '17 A Vision for our Marine Future OCEANS '17, Aberdeen, United Kingdom, 2017Conference paper, Published paper (Refereed)
Abstract [en]

Underwater imaging has become an active research area in recent years as an effect of increased interest in underwater environments and is getting potential impact on the world economy, in what is called blue growth. Since sound propagates larger distances than electromagnetic waves underwater, sonar is typically used for underwater imaging. One interesting sonar image setting is comprised of using two parts (left and right) and is usually referred to as sidescan sonar. The image resulted from sidescan sonars, which is called waterfall image, usually has to distinctive parts, the water column and the image seabed. Therefore, the edge separating these two parts, which is called the first bottom return, is the real distance between the sonar and the seabed bottom (which is equivalent to sensor primary altitude). The sensory primary altitude can be measured if the imaging sonar is complemented by interferometric sonar, however, simple sonar systems have no way to measure the first bottom returns other than signal processing techniques. In this work, we propose two methods to detect the first bottom returns; the first is based on smoothing cubic spline regression and the second is based on a moving average filter to detect signal variations. The results of both methods are compared to the sensor primary altitude and have been successful in 22 images out of 25.

Place, publisher, year, edition, pages
Aberdeen, United Kingdom: , 2017
National Category
Communication Systems
Identifiers
urn:nbn:se:mdh:diva-37336 (URN)10.1109/OCEANSE.2017.8084587 (DOI)000426997000025 ()2-s2.0-85044610106 (Scopus ID)978-1-5090-5278-3 (ISBN)
Conference
OCEANS '17 A Vision for our Marine Future OCEANS '17, 19 Jun 2017, Aberdeen, United Kingdom
Projects
Smart and networking underWAter Robots in cooperation MesheSDPAC - Dependable Platforms for Autonomous systems and Control
Available from: 2017-11-28 Created: 2017-11-28 Last updated: 2018-04-12Bibliographically approved
Rodríguez-Molina, J., Bilbao, S., Martínez, B., Frasheri, M. & Curuklu, B. (2017). An optimized, data distribution service-based solution for reliable data exchange among autonomous underwater vehicles. Sensors, 17(8), Article ID 1802.
Open this publication in new window or tab >>An optimized, data distribution service-based solution for reliable data exchange among autonomous underwater vehicles
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2017 (English)In: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, Vol. 17, no 8, article id 1802Article in journal (Refereed) Published
Abstract [en]

Major challenges are presented when managing a large number of heterogeneous vehicles that have to communicate underwater in order to complete a global mission in a cooperative manner. In this kind of application domain, sending data through the environment presents issues that surpass the ones found in other overwater, distributed, cyber-physical systems (i.e., low bandwidth, unreliable transport medium, data representation and hardware high heterogeneity). This manuscript presents a Publish/Subscribe-based semantic middleware solution for unreliable scenarios and vehicle interoperability across cooperative and heterogeneous autonomous vehicles. The middleware relies on different iterations of the Data Distribution Service (DDS) software standard and their combined work between autonomous maritime vehicles and a control entity. It also uses several components with different functionalities deemed as mandatory for a semantic middleware architecture oriented to maritime operations (device and service registration, context awareness, access to the application layer) where other technologies are also interweaved with middleware (wireless communications, acoustic networks). Implementation details and test results, both in a laboratory and a deployment scenario, have been provided as a way to assess the quality of the system and its satisfactory performance. 

Place, publisher, year, edition, pages
MDPI AG, 2017
National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-36242 (URN)10.3390/s17081802 (DOI)000408576900105 ()28783049 (PubMedID)2-s2.0-85026898497 (Scopus ID)
Available from: 2017-08-17 Created: 2017-08-17 Last updated: 2019-06-18Bibliographically approved
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