In this paper, we provide a simple, model-free algorithm for stabilizing fully observed dynamical systems.

In Table S3, we further explore the influence of the memory capacity, i.e ., the amount

With a similar goal of sharpening representation, later Transformer-style solutions [7-9,88, 89] empower attentive networks with, for instance, local contiguity [7] and multi-level feature aggregation [9,10].

Learning (GCL) frameworks are hampered by the specificity, complexity, and incompleteness of their GA techniques.

Computational social choice is a research area at the intersection of social choice (the science of collective decision-making) and computer science, which focuses on the algorithmic analysis of problems related topreference aggregation and elicitation(Brandt etal.,2013).

A temporal point process is a mathematical model for a time series of discrete events, which covers various applications. Recently, recurrent neural network (RNN) based models have been developed for point processes and have been found effective.

This paper investigates posterior sampling algorithms for competitive reinforcement learning (RL) in the context of general function approximations.