Abstract
Selecting goals and successfully pursuing them in an uncertain and dynamic environment is an important aspect of human behaviour. In order to decide which goal to pursue at what point in time, one has to evaluate the consequences of one’s actions over future time steps by forward planning. However, when the goal is still temporally distant, detailed forward planning can be prohibitively costly. One way to select actions at minimal computational costs is to use heuristics. It is an open question how humans mix heuristics with forward planning to balance computational costs with goal reaching performance. To test a hypothesis about dynamic mixing of heuristics with forward planning, we used a novel stochastic sequential two-goal task. Comparing participants’ decisions with an optimal full planning agent, we found that at the early stages of goal-reaching sequences, in which both goals are temporally distant and planning complexity is high, on average 42% (SD = 19%) of participants’ choices deviated from the agent’s optimal choices. Only towards the end of the sequence, participant’s behaviour converged to near optimal performance. Subsequent model-based analyses showed that participants used heuristic preferences when the goal was temporally distant and switched to forward planning when the goal was close.
Highlights
Decisions of which goal to pursue at what point in time are central to everyday life [1,2,3]
An important question is how humans adjust the rule of thumb approach once they get closer to the goal. We addressed this question using a novel sequential two-goal task and analysed the choice data using a computational model which arbitrates between a rule of thumb and accurate planning
We found that participants’ decision making progressively improved as the goal came closer and that this improvement was most likely caused by participants starting to plan ahead
Summary
Decisions of which goal to pursue at what point in time are central to everyday life [1,2,3]. The decision to make is whether one should continue working towards the preferred position, or switch goals and secure the less preferred position. The risk when pursuing the preferred position is to lose out on both positions This decision dilemma ‘should I risk it and go after a big reward or play it safe and gain less?’ is typical for many decisions we have to make in real life. For many such decisions, these binary choices do not emerge suddenly and unexpectedly, but the decision maker is typically confronted with such decisions after some prolonged period of time working towards enabling different options
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