Table of Contents

Preliminaries and background.
Distributed constraint optimization problems.
Background.
The DPOP algorithm.
DPOP : a dynamic programming optimization protocol for DCOP.
H-DPOP : compacting UTIL messages with consistency techniques.
Tradeoffs.
Tradeoffs between memory/message size and number of messages.
Tradeoffs between memory/message size and solution quality.
PC-DPOP : tradeoffs between memory/message size and centralization.
Dynamics.
Dynamic problem solving with self stabilizing algorithms.
Solution stability in dynamically evolving optimization problems.
Self-interest.
Distributed VCG mechanisms for systems with self-interested users.
Budget balance. Addresses three major issues that arise in Distributed Constraint Optimization Problems (DCOP): efficient optimization algorithms, dynamic and open environments, and manipulations from self-interested users. This book introduces a series of DCOP algorithms, which are based on dynamic programming.