Results 41 to 50 of about 622,806 (277)

Robust sequential decision-making in adversarial environments

Systems Science & Control Engineering
Reinforcement learning (RL) agents often fail in adversarial environments where the Markov Decision Process (MDP) assumption of a stationary environment is violated.
Jurij Ružejnikov, Tatiana Valentine Guy
doaj   +1 more source

Minimizing Maximum Regret in Commitment Constrained Sequential Decision Making

, 2017
In cooperative multiagent planning, it can often be beneficial for an agent to make commitments about aspects of its behavior to others, allowing them in turn to plan their own behaviors without taking the agent's detailed behavior into account ...
Durfee, Edmund, Singh, Satinder, Zhang, Qi   +2 more
core   +1 more source

Sequential decision making with vector outcomes [PDF]

Proceedings of the 5th conference on Innovations in theoretical computer science, 2014
We study a multi-round optimization setting in which in each round a player may select one of several actions, and each action produces an outcome vector, not observable to the player until the round ends. The final payoff for the player is computed by applying some known function f to the sum of all outcome vectors (e.g., the minimum of all ...
Yossi Azar, Uriel Felge, Michal Feldman, Moshe Tennenholtz   +3 more
openaire   +1 more source

Stressful Events Reported by Childhood Cancer Survivors and Community Controls From the St. Jude Lifetime (SJLIFE) Cohort: A Mixed Method Study

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Introduction Characterizing stressful events reported by childhood cancer survivors experienced throughout the lifespan may help improve trauma‐informed care relevant to the survivor experience. Methods Participants included 2552 survivors (54% female; 34 years of age) and 469 community controls (62% female; 33 years of age) from the St.
Megan E. Ware, Colter K. Clayton, Fang Wang, Sedigheh Mirzaei, Kyla Shelton, Tara M. Brinkman, Victoria Willard, Katianne M. Howard Sharp, Kevin Krull, Lindsay F. Schwartz, Melissa M. Hudson, Gregory T. Armstrong, Kirsten K. Ness, Rachel T. Webster   +13 more
wiley   +1 more source

Value-based decision making via sequential sampling with hierarchical competition and attentional modulation. [PDF]

PLoS ONE, 2017
In principle, formal dynamical models of decision making hold the potential to represent fundamental computations underpinning value-based (i.e., preferential) decisions in addition to perceptual decisions.
Jaron T Colas
doaj   +1 more source

Active Sensing as Bayes-Optimal Sequential Decision Making [PDF]

, 2013
Sensory inference under conditions of uncertainty is a major problem in both machine learning and computational neuroscience. An important but poorly understood aspect of sensory processing is the role of active sensing.
Ahmad, Sheeraz, Yu, Angela J.
core   +1 more source

Patient Activation in Childhood, Adolescent, and Young Adult Cancer Survivors: Current Insights and Implications for Survivorship Care—A Systematic Review From the e‐QuoL Project

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Purpose Patient activation—encompassing knowledge, confidence, and skills in managing individual's health—is a cornerstone of person‐centered care. However, its significance among childhood, adolescent, and young adult cancer survivors (CAYACS) remains unexplored. This article examines the application of the 13‐item Patient Activation Measure (
Charlotte Demoor‐Goldschmidt, Anne Maas, Gisela Michel, Amandine Bertrand, Kristen E. T. Thornton, Martine Bellanger, Anna‐Liesa Filbert, Desiree Grabow, Monica Muraca, Katharina Roser, Sara Oberti, Jelena Roganovic, Hanne Cathrine Lie   +12 more
wiley   +1 more source

Learning and Reasoning for Robot Sequential Decision Making under Uncertainty

, 2019
Robots frequently face complex tasks that require more than one action, where sequential decision-making (SDM) capabilities become necessary. The key contribution of this work is a robot SDM framework, called LCORPP, that supports the simultaneous ...
Amiri, Saeid, Shirazi, Mohammad Shokrolah, Zhang, Shiqi   +2 more
core   +1 more source

Logic-Based Sequential Decision-Making

Proceedings of the AAAI Conference on Artificial Intelligence, 2019
Deep reinforcement learning (DRL) has gained great success by learning directly from high-dimensional sensory inputs, yet is notorious for the lack of interpretability. Interpretability of the subtasks is critical in hierarchical decision-making as it increases the transparency of black-box-style DRL approach and helps the RL practitioners to ...
Daoming Lyu, Fangkai Yang, Bo Liu, Daesub Yoon   +3 more
openaire   +2 more sources

Imaging of High‐Risk Neuroblastoma: Recommendations From SIOPEN Radiology and Nuclear Medicine Specialty Committees

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Neuroblastoma is the most common extracranial solid tumor in early childhood. Its clinical behavior is highly variable, ranging from spontaneous regression to fatal outcome despite intensive treatment. The International Society of Pediatric Oncology Europe Neuroblastoma Group (SIOPEN) Radiology and Nuclear Medicine Specialty Committees ...
Annemieke Littooij, Catia Olianti, Herve Brisse, Pier Luigi Di Paolo, Maria Garganese, Tejas Kapadia, Jurgen Schaefer, Hugh Wallace, Simon Wan, Bart de Keizer, Irmina Sefic Pasic, Julian Rogasch   +11 more
wiley   +1 more source