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Collaborative Adaptive Autonomous Agents
Mälardalen University, School of Innovation, Design and Engineering. (Robotics)
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: urn:nbn:se:mdh:diva-40255ISBN: 978-91-7485-399-5 (print)OAI: oai:DiVA.org:mdh-40255DiVA, id: diva2:1233635
Presentation
2018-09-14, Gamma, Mälardalens högskola, Västerås, 09:15 (English)
Opponent
Supervisors
Available from: 2018-07-19 Created: 2018-07-18 Last updated: 2018-07-19Bibliographically approved
List of papers
1. Towards Collaborative Adaptive Autonomous Agents
Open this publication in new window or tab >>Towards Collaborative Adaptive Autonomous Agents
2017 (English)In: ICAART: PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE, VOL 1, 2017, p. 78-87Conference paper, Published paper (Refereed)
Abstract [en]

Adaptive autonomy enables agents operating in an environment to change, or adapt, their autonomy levels by relying on tasks executed by others. Moreover, tasks could be delegated between agents, and as a result decision-making concerning them could also be delegated. In this work, adaptive autonomy is modeled through the willingness of agents to cooperate in order to complete abstract tasks, the latter with varying levels of dependencies between them. Furthermore, it is sustained that adaptive autonomy should be considered at an agent's architectural level. Thus the aim of this paper is two-fold. Firstly, the initial concept of an agent architecture is proposed and discussed from an agent interaction perspective. Secondly, the relations between static values of willingness to help, dependencies between tasks and overall usefulness of the agents' population are analysed. The results show that a unselfish population will complete more tasks than a selfish one for low dependency degrees. However, as the latter increases more tasks are dropped, and consequently the utility of the population degrades. Utility is measured by the number of tasks that the population completes during run-time. Finally, it is shown that agents are able to finish more tasks by dynamically changing their willingness to cooperate.

National Category
Computer Systems
Identifiers
urn:nbn:se:mdh:diva-34097 (URN)000413243500007 ()
Conference
9th International Conference on Agents and Artificial Intelligence 2017 ICAART, 24 Feb 2017, Porto, Portugal
Projects
EUROWEB - European Resaerch and Education Collaboration with Western BalkanDPAC - Dependable Platforms for Autonomous systems and Control
Available from: 2016-12-14 Created: 2016-12-13 Last updated: 2018-07-18Bibliographically approved
2. Adaptive Autonomy in a Search and Rescue Scenario
Open this publication in new window or tab >>Adaptive Autonomy in a Search and Rescue Scenario
(English)Conference paper, Published paper (Refereed)
National Category
Engineering and Technology Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:mdh:diva-40254 (URN)
Conference
12th IEEE International Conference on Self-Adaptive and Self-Organizing Systems
Note

Konf hålls 3-7 September 2018, Trento, Italy

Available from: 2018-07-18 Created: 2018-07-18 Last updated: 2018-07-18Bibliographically approved
3. Analysis of perceived helpfulness in adaptive autonomous agent populations
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
4. Comparison Between Static and Dynamic Willingness to Interact in Adaptive Autonomous Agents
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

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Frasheri, Mirgita

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