Balancing safety and efficiency in human decision making
The safety-efficiency dilemma describes the problem of maintaining safety during efficient exploration, and is a special case of the exploration-exploitation dilemma in the face of potentially catastrophic dangers. Conventional exploration-exploitation solutions collapse punishment and reward into a single signal, whereby early losses can be overcome by later gains. But the brain has a separate system for Pavlovian fear learning, suggesting a possible computational advantage to maintaining a specific fear memory during exploratory decision-making. In a series of simulations, we show here this promotes safe but efficient learning, and is optimised by arbitrating Pavlovian avoidance on instrumental decision-making according to uncertainty. In a human approach-withdrawal experiment, we show that this flexible avoidance model captures both choice and reaction times. These results show that the Pavlovian fear system has a more sophisticated role in decision-making that previously thought, by shaping flexible exploratory behaviour in a computationally precise manner.