Wevolver Robots in Depth - Understanding the world around you using game theory w/Nicole Immorlica

Understanding the world around you using game theory w/Nicole Immorlica

02/21/20 • 36 min

Nicole talks about game theory and how she feels that it is her way to understand the world around her.

Nicole talks about game theory, a way to understand how intelligent agents, humans or machines, interact and optimize their outcome in a particular context.

Nicole discusses how this process can be used to create user interactions that are understandable and can be used efficiently.

We also hear about how dynamic games apply to robotics and how robots deal with the ever-changing world they act in.

Nicole then talks about a trend in market design where large amounts of data about previous behavior is used to redesign the market and optimize it. We also hear about how this is used to understand how people use and interact on social media platforms.

She also shares how game theory can be used to explain behavior that is not optimal, for instance in procrastination.

This podcast is part of the Wevolver network. Wevolver is a platform & community providing engineers informative content to help them innovate.
Learn more at Wevolver.com

Nicole talks about game theory and how she feels that it is her way to understand the world around her.

Nicole talks about game theory, a way to understand how intelligent agents, humans or machines, interact and optimize their outcome in a particular context.

Nicole discusses how this process can be used to create user interactions that are understandable and can be used efficiently.

We also hear about how dynamic games apply to robotics and how robots deal with the ever-changing world they act in.

She also shares how game theory can be used to explain behavior that is not optimal, for instance in procrastination.

This podcast is part of the Wevolver network. Wevolver is a platform & community providing engineers informative content to help them innovate.
Learn more at Wevolver.com

Previous Episode

The social robot revolution w/Gabriel Skantze

Gabriel Skantze talks about how he works with human robot communication, and about how the social robot revolution makes it necessary to communicate with humans in a human ways through speech and facial expressions. This is necessary as we expand the number of people that interact with robots as well as the types of interaction.

Gabriel gives us more insight into the many challenges of implementing spoken communication for co-bots, where robots and humans work closely together. They need to communicate about the world, the objects in it and how to handle them.

We also get to hear how having an embodied system using the Furhat robot head helps the interaction between humans and the system.
Having an expressive face like the Furhat adds many improvements to how a system can communicate with people. It also improves the human engagement and understanding of what the system tries to communicate significantly.

Gabriel then talks about the how they use AI and machine learning to understand speech. Understanding an individual speaker’s way to speak, thus adapting a robot to its user can improve their communication.

As the Furhat system is used out in the field, we get valuable insights from real world situations. One such case is guiding travellers at an airport to improve their experience and make travelling more efficient for everyone.

This podcast is part of the Wevolver network. Wevolver is a platform & community providing engineers informative content to help them innovate.
Learn more at Wevolver.com

Next Episode

Computer vision for field use in agriculture and recycling w/Michael Nielsen

Michael talks about his work in computer vision for field use in agriculture and recycling.

He started out in computer vision in the agriculture space doing machine vision and 3D reconstruction of plants. He then moved to the Danish Technological Institute when they expanded their work on machine vision for field use in agriculture.

Michael worked with a fusion of sensors like stereo vision, thermography, radar, lidar and high frame rate cameras, merging multiple images for high dynamic range. All this to be able to navigate the tricky situation in a farm field where you need to navigate close to or even in what is grown. Multi-baseline cameras were also used to provide range detection over a wide range of distances.

We also learn about how he expanded his work into sorting recycling, a very challenging problem. Here the sensor fusion gives him RGB as well as depth and temperature. Adding a powerful studio flash to the setup allowed him to heat the material being sorted, making it possible to determine the material, depending on how it absorbs the heat from the flash. Michael is also working on adding cameras capable of seeing above the human range of vision to make it easy to specify which materials to pick. We also hear about the problems faced when using time of flight and sheet of light cameras. He then shares some good results using stereo vision, especially combined with blue light random dot projectors.

This podcast is part of the Wevolver network. Wevolver is a platform & community providing engineers informative content to help them innovate.

Learn more at Wevolver.com

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