Tootfinder

Markov Decision Processing Networks
Sanidhay Bhambay, Thirupathaiah Vasantam, Neil Walton
https://arxiv.org/abs/2509.24541 https://arxiv.org/pdf/2509.24541…

Markov Decision Processing Networks
We introduce Markov Decision Processing Networks (MDPNs) as a multiclass queueing network model where service is a controlled, finite-state Markov process. The model exhibits a decision-dependent service process where actions taken influence future service availability. Viewed as a two-sided queueing model, this captures settings such as assemble-to-order systems, ride-hailing platforms, cross-skilled call centers, and quantum switches. We first characterize the capacity region of MDPNs. Unli…

Position: AI Will Transform Neuropsychology Through Mental Health Digital Twins for Dynamic Mental Health Care, Especially for ADHD
Neil Natarajan, Sruthi Viswanathan, Xavier Roberts-Gaal, Michelle Marie Martel
https://arxiv.org/abs/2510.07409

Position: AI Will Transform Neuropsychology Through Mental Health Digital Twins for Dynamic Mental Health Care, Especially for ADHD
Static solutions don't serve a dynamic mind. Thus, we advocate a shift from static mental health diagnostic assessments to continuous, artificial intelligence (AI)-driven assessment. Focusing on Attention-Deficit/Hyperactivity Disorder (ADHD) as a case study, we explore how generative AI has the potential to address current capacity constraints in neuropsychology, potentially enabling more personalized and longitudinal care pathways. In particular, AI can efficiently conduct frequent, low-level…