Future autonomous machines may build trust through emotion

Army research has extended the state-of-the-art in autonomy by providing a more complete picture of how actions and nonverbal signals contribute to promoting cooperation. Researchers suggested guidelines for designing autonomous machines such as robots, self-driving cars, drones and personal assistants that will effectively collaborate with Soldiers.

Dr. Celso de Melo, computer scientist with the U.S. Army Combat Capabilities Development Command’s Army Research Laboratory at CCDC ARL West in Playa Vista, California, in collaboration with Dr. Kazunori Teradafrom Gifu University in Japan, recently published a paper in Scientific Reports where they show that emotion expressions can shape cooperation.

Autonomous machines that act on people’s behalf are poised to become pervasive in society, de Melo said; however, for these machines to succeed and be adopted, it is essential that people are able to trust and cooperate with them.

“Human cooperation is paradoxical,” de Melo said. “An individual is better off being a free rider, while everyone else cooperates; however, if everyone thought like that, cooperation would never happen. Yet, humans often cooperate. This research aims to understand the mechanisms that promote cooperation with a particular focus on the influence of strategy and signaling.”

Strategy defines how individuals act in one-shot or repeated interaction. For instance, tit-for-tat is a simple strategy that specifies that the individual should act as his/her counterpart acted in the previous interaction.

Signaling refers to communication that may occur between individuals, which could be verbal (e.g., natural language conversation) and nonverbal (e.g., emotion expressions).

This research effort, which supports the Next Generation Combat Vehicle Army Modernization Priority and the Army Priority Research Area for Autonomy, aims to apply this insight in the development of intelligent autonomous systems that promote cooperation with Soldiers and successfully operate in hybrid teams to accomplish a mission.

“We show that emotion expressions can shape cooperation,” de Melo said. “For instance, smiling after mutual cooperation encourages more cooperation; however, smiling after exploiting others — which is the most profitable outcome for the self — hinders cooperation.”

The effect of emotion expressions is moderated by strategy, he said. People will only process and be influenced by emotion expressions if the counterpart’s actions are insufficient to reveal the counterpart’s intentions.

For example, when the counterpart acts very competitively, people simply ignore-and even mistrust-the counterpart’s emotion displays.

“Our research provides novel insight into the combined effects of strategy and emotion expressions on cooperation,” de Melo said. “It has important practical application for the design of autonomous systems, suggesting that a proper combination of action and emotion displays can maximize cooperation from Soldiers. Emotion expression in these systems could be implemented in a variety of ways, including via text, voice, and nonverbally through (virtual or robotic) bodies.”

According to de Melo, the team is very optimistic that future Soldiers will benefit from research such as this as it sheds light on the mechanisms of cooperation.

“This insight will be critical for the development of socially intelligent autonomous machines, capable of acting and communicating nonverbally with the Soldier,” he said. “As an Army researcher, I am excited to contribute to this research as I believe it has the potential to greatly enhance human-agent teaming in the Army of the future.”

The next steps for this research include pursuing further understanding of the role of nonverbal signaling and strategy in promoting cooperation and identifying creative ways to apply this insight on a variety of autonomous systems that have different affordances for acting and communicating with the Soldier.

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GitHub Discusses Growth of Actions API

GitHub Actions puts powerful CI/CD and automation directly into the developer workflow, and it became generally available just six months ago. Since then, we’ve continued to improve with artifact and dependency caching for faster workflows, self-hosted runners for greater flexibility, and the Actions API for extensibility. The community response has been amazing and we’re excited to share some new and upcoming enhancements.

Community-powered CI/CD and workflows

At its core, GitHub Actions allows you to automate any development workflow. Just like how our projects build on each other’s work through open source packages, GitHub Actions does the same thing for workflow automation. You can quickly reuse existing workflows or build on the thousands of free actions in the GitHub Marketplace. There’s an action for almost everything, including: Kubernetes deployments, linting, SMS alerts, or automatically assigning and labeling an issue—and it keeps growing every day.

  • GitHub Marketplace now has over 3,200 Actions, representing a 500% increase in less than six months. We’re especially grateful to everyone who took place in the recent GitHub Actions Hackathon, with over 700 submissions. Check out a few of our favorites.
  • There’s a growing and extensive ecosystem, thanks to our partners. It’s great to see how they’re expanding the ways developers can deploy their code, with new Actions from DigitalOcean, Tencent Cloud, HashiCorp, and Docker.

We’re thrilled to see how GitHub Actions is helping developers, teams, enterprises, and the open source community automate their workflows—so developers can spend more time writing code.

Scaling GitHub Actions for teams and enterprises

The community momentum behind GitHub Actions has been tremendous, and we’ve seen quick adoption with teams and enterprise customers. We want to highlight new, enterprise-focused features for GitHub Actions.

Share self-hosted runners across an organization

Now, organizations can share and manage self-hosted runners across their organization using new policies and labels. This enables large teams and enterprises to centralize the management of their core infrastructure.

  • Organization self-hosted runners make it easier for multiple repositories to reuse a set of runners. This ensures runner environments are correctly configured for the organization, resources are used efficiently, and errors resulting in extra work are avoided.
  • Custom runner labels are used to route workflows to particular runners. For example, compute-intensive workflows may use custom labels to ensure they’re always run on virtual machines with eight cores.

Improvements to the daily experience

Small changes can have a big impact on the daily experience for developers. Here are a few improvements that we recently shipped:

  • Run defaults allow users to set shell and working directory defaults in their workflows, streamlining workflow files and decreasing the likelihood of errors.
  • Explicit include matrix gives more flexibility to customer-specific legs of a parallel set of jobs, commonly used for platform-specific customization.
  • Job outputs allow a workflow to easily pass data to downstream jobs, adding flexibility to how developers automate their work.

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Author: <a href="">ProgrammableWeb PR</a>



Wolf Administration Orders Closure of Non-Life-Sustaining Businesses at 8 p.m. Today, March 19

Enforcement Actions for Restaurant, Bar Dine-In Closure Began at 8 p.m., March 18

Enforcement Actions for Non-Compliance will Begin at 12:01 a.m. Saturday, March 21

Harrisburg, PA – Governor Tom Wolf today ordered all non-life-sustaining businesses in Pennsylvania to close their physical locations as of 8 p.m. today, March 19, to slow the spread of COVID-19. Enforcement actions against businesses that do not close physical locations will begin at 12:01 a.m. Saturday, March 21.

Read Gov. Wolf’s order.

Watch a video statement from Gov. Wolf