Self-managing agents for dynamic scheduling in manufacturing

The main purpose of this paper is to propose a Multi-Agent Autonomic and Bio-Inspired based framework with selfmanaging capabilities to solve complex scheduling problems using cooperative negotiation. Scheduling resolution requires the intervention of highly skilled human problem-solvers. This is a very hard and challenging domain because current systems are becoming more and more complex, distributed, interconnected and subject to rapidly changing. A natural Autonomic Computing (AC) evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. Categories and Subject Descriptors I.2 [Artificial Intelligence]: I.2.8 Problem Solving, Control Methods, and Search – Scheduling. I.2.11 Distributed Artificial Intelligence - Multiagent systems. General Terms Algorithms, Design. Keywords Autonomic Computing, Multi-Agent Systems, Bio-Inspired Techniques, Dynamic Scheduling

• Type: Conference
• Year: 2008
• Where: GECCO
• Authors: Ana Madureira, Filipe Santos, Ivo Pereira
• Keywords: Autonomic Computing, Bio-Inspired Based Framework, Complex Scheduling Problems, GECCO 2008, Optimization