Authors:
Stefan Edelkamp
and
Christoph Greulich
Affiliation:
University of Bremen, Germany
Keyword(s):
Multiagent System Simulation, Optimization, Monte-Carlo Tree Search, Manufacturing.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Bioinformatics
;
Biomedical Engineering
;
Distributed and Mobile Software Systems
;
Enterprise Information Systems
;
Formal Methods
;
Informatics in Control, Automation and Robotics
;
Information Systems Analysis and Specification
;
Intelligent Control Systems and Optimization
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Multi-Agent Systems
;
Operational Research
;
Planning and Scheduling
;
Simulation
;
Simulation and Modeling
;
Software Engineering
;
State Space Search
;
Symbolic Systems
;
Task Planning and Execution
Abstract:
In manufacturing there are not only flow lines with stations arranged one behind the other, but also more
complex networks of stations where assembly operations are performed. The considerable difference from
sequential flow lines is that a partially ordered set of required components are brought together in order to form
a single unit at the assembly stations in a competitive multiagent system scenario. In this paper we optimize
multiagent control for such flow production units with recent advances of Nested Monte-Carlo Search. The
optimization problem is implemented as a single-agent game in a generic search framework. In particular, we
employ Nested Monte-Carlo Search with Rollout Policy Adaptation and apply it to a modern flow production
unit, comparing it to solutions obtained with a simulator and with a model checker.