AI News, Kris Hauser

Reports on the 2014 AAAI Fall Symposium Series

The AAAI 2014 Fall Symposium Series was held Thursday through Saturday, November 13–15, at the Westin Arlington Gateway in Arlington, Virginia adjacent to Washington, DC.

The titles of the seven symposia were Artificial Intelligence for Human-Robot Interaction, Energy Market Prediction, Expanding the Boundaries of Health Informatics Using AI, Knowledge, Skill, and Behavior Transfer in Autonomous Robots, Modeling Changing Perspectives: Reconceptualizing Sensorimotor Experiences, Natural Language Access to Big Data, and The Nature of Humans and Machines: A Multidisciplinary Discourse.

The highlights of each symposium are presented in this report.

RI Seminar: Kris Hauser : Beyond Geometric Path Planning

Beyond Geometric Path Planning: Paradigms and algorithms for modern robotics Kris Hauser Associate Professor, Duke University February 03, 2017 Abstract ...

Kris Hauser

Task and Motion Planning under Partial Observability - Sussman Anomaly

TAMP policy optimization on a partially observable variation of the Sussman anomaly. More details in ICRA paper: ...

RI Seminar: Peter Stone : Robot Skill Learning: From the Real World to Simulation and Back

Peter Stone David Bruton, Jr. Centennial Professor, The University of Texas at Austin Abstract For autonomous robots to operate in the open, dynamically ...

Computational Geometry Lecture 23: Motion planning

Digital Transformation: Interview with Peter Stone, Pioneer in Machine Learning and Robotics

Digital Transformation, A Project by Manuel Stagars For interviews about the brave new world of blockchain technology ..

Will AI violate human rights? Humanitarian groups are trying to make sure they don’t

A group of human rights organizations has signed the Toronto Declaration on Machine Learning, an initiative that calls for regulations designed to protect people ...

RI Seminar : Pieter Abbeel : Machine Learning and Optimization for Robotics

Pieter Abbeel Assistant Professor, Department of Electrical Engineering and Computer Science, UC Berkeley October 18, 2013 Abstract Robots are typically far ...