In reinforcement learning, an agent interacts with its environment to act according to a policy in accordance with the observation state; these are executed based on a class of neural networks. In the interaction between states and actions, the series of decision sequences are often described...

Models of social learning feature either binary signals or abstract signal structures often deprived of micro-foundations. Both models are limited when analyzing interim results or performing empirical analysis. We present a method of generating signal structures which are richer than the binary...

This paper deals with processes that require several complementary inputs subject to improvements in quality. If after a quality upgrade one of these inputs requires a period of learning before it can be used effectively, then in general it will pay to purchase the inputs at different dates --...

In misspecified environments, should an economic agent act rationally towards optimizing some goal? If so, what should that goal be? Prior work has focused on the goal of bidirectional consistency of beliefs and actions, in effect finding a Nash equilibrium of an imaginary game in which one...

We propose a distributed randomized policy iteration algorithm for infinite horizon dynamic programming problems for which the control at each stage is m-dimensional. The traditional policy iteration algorithm involves performing a minimization over an m-dimensional constraint set and has a...

This paper studies the Random Utility Model (RUM) in a repeated stochastic choice situation, in which the decision maker is imperfectly informed about the payoffs associated to each of the available alternatives. By embedding the RUM into an online decision problem, we develop a gradient-based...

Team-competition in multi-agent games is an important setting, where multi-agent actor-critic methods are the state-of-the-art methods. In many such scenarios, the roles for players naturally emerge, thus aiding in collaboration within the teams. However, exiting methods for the team-competition...

This study aims to determine the effect of reading interest, learning discipline, and learning motivation on student learning outcomes. This type of research is quantitative. The sample in this study was students in 2019, 2020, and 2021. The instrument used in this study was a questionnaire with...

This research was conducted with the aim of knowing how the influence of learning facilities, learning motivation, and learning discipline on student achievement in Office Administration, Faculty of Economics, State University of Jakarta. The type of research used is quantitative method with...

This study aims to see the effect of study habits, interest in learning, and learning environment on learning achievement. This study uses quantitative methods with a research sample of 233 people.The results of this study indicate that the influence of study habits providespositive results on...