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Kyle Palko

2 accepted papers

2022

Interpretable Autonomous Flight Via Compact Visualizable Neural Circuit Policies

RA-L 2022

We learn interpretable end-to-end controllers based on Neural Circuit Policies (NCPs) to enable goal reaching and dynamic obstacle avoidance in flight domains. In addition to being able to learn high-quality control, NCP networks are designed with a small number of neurons. This property allows for

Cited by 8SourceScholar
2021

Evaluation of Human-AI Teams for Learned and Rule-Based Agents in Hanabi

NeurIPS 2021poster

Deep reinforcement learning has generated superhuman AI in competitive games such as Go and StarCraft. Can similar learning techniques create a superior AI teammate for human-machine collaborative games? Will humans prefer AI teammates that improve objective team performance or those that improve su…

Cited by 74SourcePDFScholar