Interestingly there was a recent neuroscience paper that basically said “our computational model of the brain includes this part about mental effort but we have no damn idea why anything should require mental effort, we put it in our model because obviously that’s a thing with humans but no theory would predict it”:
Unlike the principles of hierarchy and world models, a cost principle was introduced into ACC models primarily for empirical rather than computational reasons. Empirically, the deployment of high-level control over task-execution appears to incur a cost that, phenomenologically, is experienced as effortful and is therefore aversive, and hence is minimized according to a cost-benefit tradeoff [34]. Such a cost was implicit in the seminal response conflict model of ACC, which incorporated a self-regulating control mechanism that increased control only when it was needed [7]. More recent models of ACC have explicitly accounted for the cost of control in regulating effortful behaviors (e.g., [35,36]). For example, in line with recent behavioral evidence [37], the HRL model of ACC regulates control at multiple levels of hierarchy, disengaging when control is not required to maintain a high average reward rate [15].
Yet despite the empirical evidence, this principle provides no obvious benefit to the agent: selfregulating control would appear to be both computationally [38] and evolutionarily [39] maladaptive. Accordingly, it is unclear whether the cost of control is a “bug” or a “feature” of the system. On one side, the bug view proposes that the cost reflects biophysical constraints. For example, self-control could consume a limited glucose supply, though this hypothesis has been vigorously disputed [40]. The exercise of control could also temporarily deplete neurotransmitter levels such as dopamine [36], and/or contribute to the buildup in the brain of toxic waste products like amyloid-beta [38]. In these cases, the relaxation of control would prevent against these negative outcomes.
Alternatively, the feature view proposes computational constraints to control. For example, it has been argued that to accommodate opportunity costs incurred when the value of an alternative task exceeds that of the current task, the relaxation of control facilitates a task switch [41]. However, there is no obvious reason why opportunity costs should impair task performance before the switch. Likewise, capacity constraints associated with difficult neural computations, such as interfering task representations [42], do not address why control over any single task should vary over time. Another possibility is that, when control is not required because the task is very easy, control can actually impair performance by slowing it down [43]. However, this explanation does not address why control sometimes wanes on difficult tasks wherein control is always advantageous.
Taken together, these considerations indicate that ACC self-regulates control levels in order to minimize a concomitant cost, the source of which remains a vexing question in cognitive neuroscience.
Under the bidding system theory, if the non-winning bids still have to pay out some fraction of the amount bid even when they lose, then bidding wars are clearly costly. Even when the executive control agent is winning all the bids, resources are being drained every auction in some proportion to how strongly other agents are still bidding. This seems to align with my own perceptions at first glance and explains how control wanes over time.
Interestingly there was a recent neuroscience paper that basically said “our computational model of the brain includes this part about mental effort but we have no damn idea why anything should require mental effort, we put it in our model because obviously that’s a thing with humans but no theory would predict it”:
Under the bidding system theory, if the non-winning bids still have to pay out some fraction of the amount bid even when they lose, then bidding wars are clearly costly. Even when the executive control agent is winning all the bids, resources are being drained every auction in some proportion to how strongly other agents are still bidding. This seems to align with my own perceptions at first glance and explains how control wanes over time.