Analysis of Perceived Helpfulness in Adaptive Autonomous Agent Populations

Frasheri, Mirgita; Çürüklü, Baran; Ekström, Mikael

doi:10.1007/978-3-319-78301-7_10

Cited by 3 publications

(7 citation statements)

References 32 publications

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“…Our overall vision for the use of test agents is to shift the bulk of continuous test selection, prioritisation and scheduling from a centralized regression test automation framework to a lower level of abstraction where test agents can decide by themselves how and what to execute. An adaptive autonomous agent proposed by Frasheri et al [20] has been modified to fit the purposes of a testing agent. Such an agent can be described from two perspectives, its overall internal operation, and the interaction mechanisms which enable adaptive autonomous behaviour.…”

Section: Defining a Test Agentmentioning

confidence: 99%

Test Agents: The Next Generation of Test Cases

Enoiu

Frasheri

2019

2019 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)

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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.

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Section: Defining a Test Agentmentioning

confidence: 99%

Test Agents: The Next Generation of Test Cases

Enoiu

Frasheri

2019

2019 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)

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“…In this Section, the agent model proposed in [3], is revised, and the proposed adaptation strategy for AA is described.…”

Section: The Adaptation Strategymentioning

confidence: 99%

“…Adaptive autonomous behavior is modeled through the willingness to interact, composed of two components referred to as the willingness to ask for, and give help [3]. The willingness to ask for help represents the likelihood with which an agent will ask another agent for help during the execution of a task (execute state).…”

Section: B Willingness To Interactmentioning

confidence: 99%

“…In order to calculate the corrections u and v, nine factors (n = 9) have been identified in [3] as relevant in the process of deciding when to ask and give help during runtime. All the factors follow the update rules (5) and (6).…”

Section: Factor Descriptionmentioning

confidence: 99%

“…This paper deals with the development of local reasoning mechanisms, adapting the level of cooperation among agents based on several factors in order to improve the overall performance. To this end, AA is modeled herein through the willingness to interact [3], which allows agents to decide when to give or ask for help. AA behavior is relevant in those scenarios in which agents should be able to solve issues locally-especially when assistance from human operators is not available, e.g., due to unreliable communication channels.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive Autonomy in a Search and Rescue Scenario

Frasheri

Çürüklü

Esktrom

et al. 2018

2018 IEEE 12th International Conference on Self-Adaptive and Self-Organizing Systems (SASO)

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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 ROSbased multi agent system, and results show that the proposed adaptation strategy provides a more stable performance than a static collaboration policy.

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Test Agents: Adaptive, Autonomous and Intelligent Test Cases

Enoiu,

Frasheri

2018

Preprint

Self Cite

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Growth of so ware 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 so ware resources dedicated to test automation, so ware testing is faced with enormous challenges, resulting in increased dependence on complex mechanisms for automated test case selection and prioritization as part of a continuous integration framework. ese mechanisms are currently using simple entities called test cases that are concretely realized as executable scripts. Our key idea is to provide test cases with more reasoning, adaptive behavior and learning capabilities by using the concepts of intelligent so ware agents. We refer to such test cases as test agents. e model that underlie a test agent is capable of exible and autonomous actions in order to meet overall testing objectives. Our goal is to increase the decentralization of regression testing by le ing 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 soware test agents that display such adaptive autonomous behavior. Emerging developments and challenges regarding the use of test agents are explored-in particular, new research that seeks to use adaptive autonomous agents in so ware testing.

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Analysis of Perceived Helpfulness in Adaptive Autonomous Agent Populations

Cited by 3 publications

References 32 publications

Test Agents: The Next Generation of Test Cases

Test Agents: The Next Generation of Test Cases

Adaptive Autonomy in a Search and Rescue Scenario

Test Agents: Adaptive, Autonomous and Intelligent Test Cases

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