Resource constrained distributed constraint optimization using resource constraint free pseudo-tree

نویسندگان

  • Toshihiro Matsui
  • Marius-Calin Silaghi
  • Katsutoshi Hirayama
  • Makoto Yokoo
  • Hiroshi Matsuo
چکیده

The Distributed Constraint Optimization Problem (DCOP) is a fundamental formalism for multi-agent cooperation. A dedicated framework called Resource Constrained DCOP (RCDCOP) has recently been proposed. RCDCOP models objective functions and resource constraints separately. A resource constraint is an n-ary constraint that represents the limit on the number of resources of a given type available to agents. Previous research addressing RCDCOPs employs the Adopt algorithm, which is a basic solver for DCOPs. In this paper we propose another version of the Adopt algorithm for RCDCOP using a pseudo-tree that is generated ignoring resource constraints. The key ideas of our work are as follows: (i) The pseudo-tree is generated ignoring resource constraints. (ii) Virtual variables are introduced, representing the usage of resources. These virtual variables are used to share resources among subtrees. These ideas are used to extend Adopt. The proposed method reduces the previous limitations in the construction of RCDCOP pseudo-trees. The efficiency of our technique depends on the class of problems being considered, and we describe the obtained experimental results.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Resource constrained DCOP solver using virtual variables and conventional pseudo-tree

The Distributed Constraint Optimization Problem (DCOP) is a fundamental formalism for multi-agent cooperation. With DCOPs, the agent states and the relationships between agents are formalized into a constraint optimization problem, which is then solved using distributed cooperative optimization algorithms. In the original DCOP framework, a set of objective functions is employed to represent the...

متن کامل

Resource Constrained Distributed Constraint Optimization with Virtual Variables

Cooperative problem solving with resource constraints are important in practical multi-agent systems. Resource constraints are necessary to handle practical problems including distributed task scheduling with limited resource availability. A dedicated framework called Resource Constrained DCOP (RCDCOP) has recently been proposed. RCDCOP models objective functions and resource constraints separa...

متن کامل

Resource Allocation in Sensor Networks Using Distributed Constraint Optimization

Several algorithms have been proposed for solving constraint satisfaction and the more general constraint optimization problem in a distributed manner. In this paper we apply two such algorithms to the task of dynamic resource allocation in the sensor network domain using appropriate abstractions. The aim is to effectively track multiple targets by making the sensors coordinate with each other ...

متن کامل

Resource Constrained Project Scheduling with Material Ordering: Two Hybridized Meta-Heuristic Approaches (TECHNICAL NOTE)

Resource constrained project scheduling problem (RCPSP) is mainly investigated with the objective of either minimizing project makespan or maximizing project net present value. However, when material planning plays a key role in a project, the existing models cannot help determining material ordering plans to minimize material costs. In this paper, the RCPSP incorporated with the material order...

متن کامل

Efficient Methods for Pseudo-tree Based Distributed Best First Search

Abstract— Distributed constraint optimization problem is an area of research in multi agent system. In recent years, a distributed constraint optimization algorithm, which performs best-first search in bottom up manner according to pseudo tree, was proposed. In this paper, we propose several efficient methods for the distributed bottom up best-first search. Derivation of partial solution is int...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2008