Contrasting Human and Computational Intelligence Based Autonomous Behaviors in a Blue–Red Simulation Environment Article Swipe
Shir Li Wang
,
Kamran Shafi
,
Theam Foo Ng
,
Chris Lokan
,
Hussein A. Abbass
·
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1109/tetci.2016.2641929
YOU?
·
· 2017
· Open Access
·
· DOI: https://doi.org/10.1109/tetci.2016.2641929
Autonomous systems are making their way to the market. The transition from tasks performed by humans to tasks performed by machines begs for an answer to one of the most challenging questions in this area of research: Will humans understand and trust what a machine does? Analyzing human and machine behaviors offers the foundational steps toward finding answers to this question. This paper contributes a novel methodology for transforming low-level actions by each agent into high-level categorization of strategies to contrast the behaviors of humans and machines using a computational red teaming environment with a red (evader) and a blue (pursuer) agent. Two orthogonal sources of uncertainty were examined: the uncertainty in the blue agent's situation awareness about the red, and the red agent's uncertainty resulting from deceptive actions by the blue. For each uncertainty source, two different experiments were conducted by varying the controller of the red agent. In one experiment, the red agent was controlled by one of the 34 human subjects; and in the second, by an evolved neural network. The blue agent was controlled by a scripted rule-based system. In this time-critical task, the results revealed that humans tend to follow systemic and consistent strategies, sometimes ignoring the information available to them. On the other hand, machines tend to evolve more complex and diverse strategies. This finding calls for new computational intelligence techniques to enable the fusion of these different strategies into forms that each party can understand and use effectively.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/tetci.2016.2641929
- OA Status
- hybrid
- Cited By
- 7
- References
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- Related Works
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- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W2572587835Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/tetci.2016.2641929Digital Object Identifier
- Title
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Contrasting Human and Computational Intelligence Based Autonomous Behaviors in a Blue–Red Simulation EnvironmentWork title
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2017Year of publication
- Publication date
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2017-01-17Full publication date if available
- Authors
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Shir Li Wang, Kamran Shafi, Theam Foo Ng, Chris Lokan, Hussein A. AbbassList of authors in order
- Landing page
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https://doi.org/10.1109/tetci.2016.2641929Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
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https://doi.org/10.1109/tetci.2016.2641929Direct OA link when available
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Computer science, Artificial intelligence, Task (project management), Categorization, Multi-agent system, Machine learning, Human–computer interaction, Engineering, Systems engineeringTop concepts (fields/topics) attached by OpenAlex
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7Total citation count in OpenAlex
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2025: 1, 2023: 2, 2021: 2, 2019: 1, 2017: 1Per-year citation counts (last 5 years)
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46Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| primary_location.source.host_organization_lineage_names | Institute of Electrical and Electronics Engineers |
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| publication_date | 2017-01-17 |
| publication_year | 2017 |
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