핵심 개념
Bridging human expectations with AI behavior through Safe Explicable Planning.
통계
"The optimal return in the agent’s model is 94 (i.e., moving along the edge of the cliff to the goal), while the return of the trajectory with the longest detour (i.e., staying as far away from the edge as possible) without falling off the cliff is 90, discount notwithstanding."
"The ground-truth (MR) is that the agent can travel alongside the edge without slipping off the cliff."
"The human’s belief (MH R ) is that there is a probability that the agent may slip off from the edge, especially in terrain closer to the cliff, which is more uneven and challenging to traverse."
인용구
"Our approach shows initial steps towards finding approximate safe explicable policies, with further research needed for more generalized and efficient approximation solutions."
"We conducted evaluations via simulations and physical robot experiments to validate the efficacy of our approach."