IPAB Workshop-17/09/2020 Title: Composing Diverse Policies for Robot Control Abstract: Solving long-horizon problems is a challenging task, requiring optimizing across a variety of sub-task dynamics. Learning from demonstration provides a strategy for learning a method to compose a set of already known diverse controllers, each tuned for their corresponding sub-problem. Additionally, performing causal analysis on the controllers gives us the ability to extract specifications about the demonstrated policy in regards to known symbols in the environment. Finally, to build robust controllers from demonstrations, we want to obtain a variety of possible trajectories, often limited by the comfort space of the demonstrator or the robot. We will present Learning from Inverse Intervention. A strategy for collaborative demonstration, in which the robot augments the demonstrator trajectory, pushing it to uncertain to the policy states. It results in better demonstrations, as well as the ability to elicit problem structure. Sep 17 2020 13.00 - 14.00 IPAB Workshop-17/09/2020 Daniel Angelov Blackboard Collaborate https://eu.bbcollab.com/guest/30377a70e05243929bffce87fd3c7b7c
IPAB Workshop-17/09/2020 Title: Composing Diverse Policies for Robot Control Abstract: Solving long-horizon problems is a challenging task, requiring optimizing across a variety of sub-task dynamics. Learning from demonstration provides a strategy for learning a method to compose a set of already known diverse controllers, each tuned for their corresponding sub-problem. Additionally, performing causal analysis on the controllers gives us the ability to extract specifications about the demonstrated policy in regards to known symbols in the environment. Finally, to build robust controllers from demonstrations, we want to obtain a variety of possible trajectories, often limited by the comfort space of the demonstrator or the robot. We will present Learning from Inverse Intervention. A strategy for collaborative demonstration, in which the robot augments the demonstrator trajectory, pushing it to uncertain to the policy states. It results in better demonstrations, as well as the ability to elicit problem structure. Sep 17 2020 13.00 - 14.00 IPAB Workshop-17/09/2020 Daniel Angelov Blackboard Collaborate https://eu.bbcollab.com/guest/30377a70e05243929bffce87fd3c7b7c