Department of Psychology, Technische Universität Dresden, Dresden, Germany.
PLoS Comput Biol. 2020 Feb 18;16(2):e1007685. doi: 10.1371/journal.pcbi.1007685. eCollection 2020 Feb.
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.
在不确定和动态的环境中选择目标并成功追求目标是人类行为的一个重要方面。为了决定在何时追求哪个目标,人们必须通过前瞻性规划来评估未来时间步长内行动的后果。然而,当目标仍然具有时间间隔时,详细的前瞻性规划可能会非常昂贵。以最低的计算成本选择行动的一种方法是使用启发式。人类如何将启发式与前瞻性规划混合以平衡计算成本与目标达成绩效是一个悬而未决的问题。为了测试关于启发式与前瞻性规划动态混合的假设,我们使用了一种新颖的随机顺序双目标任务。将参与者的决策与最优的完整规划代理进行比较,我们发现,在目标达成序列的早期阶段,两个目标都具有时间间隔,并且规划复杂性很高,平均有 42%(SD=19%)的参与者选择偏离代理的最优选择。只有在序列的最后阶段,参与者的行为才接近最优表现。随后的基于模型的分析表明,当目标具有时间间隔时,参与者使用启发式偏好,而当目标接近时,他们会切换到前瞻性规划。