A Novel Quantum Approach to the Dynamics of Decision Making
Abstract
We present a new quantum-markovian model of two-alternative forced choice (2AFC) decision-making. We treatthe decision-making process as an accumulation of evidencebetween two competing alternatives, analogous to the drift dif-fusion model (DDM), in which the stimulus acts as a gener-ative process, emitting bits of information that are treated asquantum particles. The particles are acted on by a landscapedetermined by the agent’s experience with the task or stimu-lus, signal strength, and allocated cognitive control. We de-rive closed form expressions for success rates under both theinterrogation and free response paradigms. Under the free re-sponse paradigm, we show that this model reduces to a Markovprocess with closed form response time (RT) distributions thattake the form of inverse gaussians (IGs) with periodic noisecharacteristic to the task set. In the limit of long RT, the RTdistributions become smooth, recovering true IG distributionsanalogous to the standard DDM.