Resilience for Goal-Based Agents: Formalism, Metrics, and Case Studies
Goal-based agents need to be resilient to perturbations in the world. Existing resilience definitions emphasize maintenance-type goals and, consequently, describe how well systems can recover and return to a desirable operating state after a perturbation. An alternative formulation of resilience is...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10290878/ |
| _version_ | 1797634007512383488 |
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| author | Jennifer Leaf Julie A. Adams Matthias Scheutz Michael A. Goodrich |
| author_facet | Jennifer Leaf Julie A. Adams Matthias Scheutz Michael A. Goodrich |
| author_sort | Jennifer Leaf |
| collection | DOAJ |
| description | Goal-based agents need to be resilient to perturbations in the world. Existing resilience definitions emphasize maintenance-type goals and, consequently, describe how well systems can recover and return to a desirable operating state after a perturbation. An alternative formulation of resilience is required for achievement-type goals that emphasize the ability to progress towards a goal state. This manuscript proposes a new formalism of resilience as a computational construct that accounts for an agent’s sensors, effectors, communication channels, and computational resources. Two metrics for comparing the resilience of different algorithms are derived, namely power and efficiency. Three case studies demonstrate how the metrics can be used to characterize power-efficiency tradeoffs in algorithm design. A common property of the resilient algorithms in the case studies is that they have the ability to exploit many possible world trajectories, often at the cost of failing to find optimal trajectories in unperturbed conditions. |
| first_indexed | 2024-03-11T12:02:44Z |
| format | Article |
| id | doaj.art-7eae6508aa454d059c861638693f12f6 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-11T12:02:44Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-7eae6508aa454d059c861638693f12f62023-11-08T00:01:10ZengIEEEIEEE Access2169-35362023-01-011112199912201510.1109/ACCESS.2023.332675510290878Resilience for Goal-Based Agents: Formalism, Metrics, and Case StudiesJennifer Leaf0https://orcid.org/0000-0002-4979-1435Julie A. Adams1https://orcid.org/0000-0002-7774-728XMatthias Scheutz2https://orcid.org/0000-0002-0064-2789Michael A. Goodrich3https://orcid.org/0000-0002-2489-5705Collaboative Robotics and Intelligent Systems Institute, Oregon State University, Corvallis, OR, USACollaboative Robotics and Intelligent Systems Institute, Oregon State University, Corvallis, OR, USADepartment of Computer Science, Tufts University, Medford, MA, USADepartment of Computer Science, Brigham Young University, Provo, UT, USAGoal-based agents need to be resilient to perturbations in the world. Existing resilience definitions emphasize maintenance-type goals and, consequently, describe how well systems can recover and return to a desirable operating state after a perturbation. An alternative formulation of resilience is required for achievement-type goals that emphasize the ability to progress towards a goal state. This manuscript proposes a new formalism of resilience as a computational construct that accounts for an agent’s sensors, effectors, communication channels, and computational resources. Two metrics for comparing the resilience of different algorithms are derived, namely power and efficiency. Three case studies demonstrate how the metrics can be used to characterize power-efficiency tradeoffs in algorithm design. A common property of the resilient algorithms in the case studies is that they have the ability to exploit many possible world trajectories, often at the cost of failing to find optimal trajectories in unperturbed conditions.https://ieeexplore.ieee.org/document/10290878/Resilienceperturbationssingle goalagentsrobots |
| spellingShingle | Jennifer Leaf Julie A. Adams Matthias Scheutz Michael A. Goodrich Resilience for Goal-Based Agents: Formalism, Metrics, and Case Studies IEEE Access Resilience perturbations single goal agents robots |
| title | Resilience for Goal-Based Agents: Formalism, Metrics, and Case Studies |
| title_full | Resilience for Goal-Based Agents: Formalism, Metrics, and Case Studies |
| title_fullStr | Resilience for Goal-Based Agents: Formalism, Metrics, and Case Studies |
| title_full_unstemmed | Resilience for Goal-Based Agents: Formalism, Metrics, and Case Studies |
| title_short | Resilience for Goal-Based Agents: Formalism, Metrics, and Case Studies |
| title_sort | resilience for goal based agents formalism metrics and case studies |
| topic | Resilience perturbations single goal agents robots |
| url | https://ieeexplore.ieee.org/document/10290878/ |
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