Probabilistic reasoning in multiagent systems: a graphical models approach

✍ Scribed by Xiang, Yang

Publisher: Cambridge University Press
Year: 2004
Tongue: English
Leaves: 308
Category: Library

No coin nor oath required. For personal study only.

✦ Table of Contents

Preface
1. Introduction
2. Bayesian networks
3. Belief updating and cluster graphs
4. Junction tree representation
5. Belief updating with junction trees
6. Multiply sectioned Bayesian networks
7. Linked junction forests
8. Distributed multi-agent inference
9. Model construction and verification
10. Looking into the future
Bibliography
Index.

✦ Subjects

Bayesian statistical decision theory--Data processing;Distributed artificial intelligence;Intelligent agents (Computer software);Electronic books;Bayesian statistical decision theory -- Data processing

📜 SIMILAR VOLUMES

Probabilistic Reasoning in Multiagent Sy

📁 Probabilistic Reasoning in Multiagent Systems : A Graphical Models Approach

✍ Yang Xiang 📂 Library 📅 2002 🏛 Cambridge University Press 🌐 English

Probabilistic Reasoning in Multiagent Sy

📁 Probabilistic Reasoning in Multiagent Systems: A Graphical Models Approach

✍ Yang Xiang 📂 Library 📅 2002 🏛 Cambridge University Press 🌐 English

Probalistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become an active field of research and practice in artifical intelligence, operations research and statistics in the last two decades. The success of this technique in modeling intelligent decision s

Modeling and Analysis of Dependable Syst

📁 Modeling and Analysis of Dependable Systems: A Probabilistic Graphical Model Perspective

✍ Luigi Portinale, Daniele Codetta Raiteri 📂 Library 📅 2015 🏛 World Scientific Publishing Company 🌐 English

The monographic volume addresses, in a systematic and comprehensive way, the state-of-the-art dependability (reliability, availability, risk and safety, security) of systems, using the Artificial Intelligence framework of Probabilistic Graphical Models (PGM). After a survey about the main concepts a

Reasoning with Probabilistic and Determi

📁 Reasoning with Probabilistic and Deterministic Graphical Models. Exact Algorithms

✍ Rina Dechter 📂 Library 📅 2019 🏛 Morgan & Claypool 🌐 English

Reasoning with Probabilistic and Determi

📁 Reasoning with Probabilistic and Deterministic Graphical Models: Exact Algorithms

✍ Rina Dechter 📂 Library 📅 2019 🏛 Springer 🌐 English

<p><span>Graphical models (e.g., Bayesian and constraint networks, influence diagrams, and Markov decision processes) have become a central paradigm for knowledge representation and reasoning in both artificial intelligence and computer science in general. These models are used to perform many reaso

Reasoning with Probabilistic and Determi

📁 Reasoning with Probabilistic and Deterministic Graphical Models: Exact Algorithms

✍ Rina Dechter 📂 Library 📅 2022 🏛 Springer 🌐 English