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A Risk-Sensitive Approach to Policy Optimization
Without cost constraints, we find that pessimistic risk profiles can be used to reduce cost while improving total reward accumulation.
A Risk-Sensitive Policy Gradient Method
Standard deep reinforcement learning (DRL) agents aim to maximize expected reward, considering collected experiences equally in formulating a policy.
Assured Autonomy: Path Toward Living With Autonomous Systems We Can Trust
The second workshop held in February 2020, focused on existing capabilities, current research, and research trends that could address the challenges and problems identified in workshop.
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