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
Introduction to Machine Learningby Amnon Shashua - arXiv
Introduction to Machine learning covering Statistical Inference (Bayes, EM, ML/MaxEnt duality), algebraic and spectral methods (PCA, LDA, CCA, Clustering), and PAC learning (the Formal model, VC dimension, Double Sampling theorem).
(22217 views)
Elements of Causal Inference: Foundations and Learning Algorithmsby J. Peters, D. Janzing, B. Schölkopf - The MIT Press
This book offers a self-contained and concise introduction to causal models and how to learn them from data. The book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from data ...
(6149 views)
Statistical Foundations of Machine Learningby Gianluca Bontempi, Souhaib Ben Taieb
This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data. This manuscript aims to find a good balance between theory and practice.
(9181 views)
A First Encounter with Machine Learningby Max Welling - University of California Irvine
The book you see before you is meant for those starting out in the field of machine learning, who need a simple, intuitive explanation of some of the most useful algorithms that our field has to offer. A prelude to the more advanced text books.
(12292 views)