Topic: discrete-state Markov process

Our understanding of how the brain makes decisions has benefited greatly from normative theories that have, for example, established benchmarks for how specific forms of evidence accumulation and decision rules can optimally balance quantities like decision speed and accuracy. These theories have recently been expanded to include adaptive components that are necessary for effective decision making in dynamic environments. However, these extensions remain incomplete, because they have focused primarily on how an unconstrained agent manages single, independent decisions [1]. In contrast, real-wo