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A class of algorithms for distributed constraint optimization [electronic resource] / Adrian Petcu.

By: Contributor(s): Material type: TextTextSeries: Frontiers in artificial intelligence and applications ; v. 194. | Frontiers in artificial intelligence and applications. Dissertations in artificial intelligence.Publication details: Amsterdam : IOS Press, c2009.Description: 1 online resource (xxiii, 274 p.) : illISBN:
  • 9781607504184
  • 1607504189
  • 9781441616630 (electronic bk.)
  • 1441616632 (electronic bk.)
Subject(s): Genre/Form: Additional physical formats: Print version:: Class of algorithms for distributed constraint optimization.DDC classification:
  • 004 22
LOC classification:
  • QA76.612 .P48 2009eb
Online resources:
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.
Summary: 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.
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Includes bibliographical references.

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.

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