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HEATlab Papers Published by ICAPS

Last summer, the students in computer science professor Jim Boerkoel鈥檚 Human Experience & Agent Teamwork Lab (HEATLab) studied several aspects of human-robot interaction and wrote up their findings. This summer, they will celebrate the publication of three papers at the International Conference on Automated Planning and Scheduling (ICAPS) in Berkeley, California.

鈥淚 really didn鈥檛 expect this,鈥� says Boerkoel of the exciting news that all three papers were selected. 鈥淚t鈥檚 a testament to how awesome my students are.鈥�

Shyan Akmal 鈥�19, Savana Ammons 鈥�20, Maggie Li 鈥�19 (鈥淨uantifying Degrees of Controllability in Temporal Networks with Uncertainty鈥�), Joon Lee 鈥�20, Viva Ojha 鈥�19 (鈥淢easuring and Optimizing Durability Against Scheduling Disturbances鈥�) and Jordan Abrahams 鈥�19 (鈥淩educing the Computational and Communication Overhead of Robust Agent Rescheduling鈥�) were members of the summer 2018 HEATLab team.

In addition to being pleasantly surprised at the number of accepted papers, Boerkoel is also impressed with how quickly these papers came together. 鈥淚n this case, two of the three papers were started and finished during the 10-week summer session. Our students are just really well-versed at the skills required for effectively carrying out and communicating research. I鈥檇 compare them to second- and third-year PhD students in terms of preparation and productivity.鈥�

Here鈥檚 a summary of the papers:

鈥淨uantifying Degrees of Controllability in Temporal Networks with Uncertainty鈥�
Shyan Akmal 鈥�19, Savana Ammons 鈥�20, Maggie Li 鈥�19 launched a new student-led project that looks to deal with situations where scheduling uncertainty outstrips an agent鈥檚 ability to control for it. They developed new analytical tools for assessing what they coined 鈥渢he degree of controllability,鈥� which measures the likelihood that an agent (e.g., robot) can control for the presence of scheduling uncertainty (due to, e.g., slippage or localization error). In addition to these new analytical tools, they also developed and empirically validated approximate methods for finding scheduling strategies that maximize likelihood of success.

鈥淢easuring and Optimizing Durability Against Scheduling Disturbances鈥�
Joon Lee 鈥�20 and Viva Ojha 鈥�19 use geometric interpretations of scheduling problems to develop new ways to quantify a schedule鈥檚 resilience to unexpected scheduling disturbances. In particular, they defined a new concept, 鈥渄urability,鈥� which characterizes a temporal plan鈥檚 resilience to disturbances. They also proposed several durability metrics and two new approaches for finding optimally durable schedules. An additional contribution was an empirical model for simulating realistic sources of schedule uncertainty, which they used to perform a systematic empirical evaluation of proposed metrics and approaches.

鈥淩educing the Computational and Communication Overhead of Robust Agent Rescheduling鈥�
Jordan Abrahams 鈥�19 and co-author Jeremy Frank built on the work of the 2017鈥�2018 NASA Ames Research鈥檚 HMC Computer Science Clinic team to explore how they could adapt uncertainty-aware, dynamic scheduling advice to be more judicious in how often rescheduling, and, by extension, communication, was required in multi-agent settings. In particular, they introduced a single streamlined algorithm that trades robustness for various forms of computational overhead including multi-agent communication. In addition to these algorithmic advances, they contribute a systematic, thorough empirical evaluation that significantly improves the understanding of this space of tradeoffs.