Modeling Agents with Probabilistic Programs
by Owain Evans, et al.
Publisher: AgentModels.org 2017
Number of pages: 345
Description:
This book describes and implements models of rational agents for (PO)MDPs and Reinforcement Learning. One motivation is to create richer models of human planning, which capture human biases and bounded rationality. The book assumes basic programming experience but is otherwise self-contained.
Download or read it online for free here:
Read online
(online html)
Similar books

by Albert Bifet, et al. - The MIT Press
This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA, allowing readers to try out the techniques after reading the explanations.
(4582 views)

by Jonas Buchli, et al. - arXiv.org
The starting point is the formulation of of an optimal control problem and deriving the different types of solutions and algorithms from there. These lecture notes aim at supporting this unified view with a unified notation wherever possible.
(4453 views)

by Ratnadip Adhikari, R. K. Agrawal - arXiv
This work presents a concise description of some popular time series forecasting models used in practice, with their features. We describe three important classes of time series models, viz. the stochastic, neural networks and SVM based models.
(9870 views)

by Richard S. Sutton, Andrew G. Barto - The MIT Press
The book provides a clear and simple account of the key ideas and algorithms of reinforcement learning. It covers the history and the most recent developments and applications. The only necessary mathematical background are concepts of probability.
(24548 views)