Authors:
Hanno Hildmann
and
Miquel Martin
Affiliation:
NEC Laboratories Europe, Germany
Keyword(s):
Resource Allocation, Scheduling, Emergence, Optimization, Stochastic Optimization, Routing, Logistics.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
e-Business
;
Enterprise Information Systems
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Logistics
;
Methodologies and Technologies
;
Operational Research
;
Optimization
;
OR in Transportation
;
Pattern Recognition
;
Resource Allocation
;
Routing
;
Scheduling
;
Software Engineering
;
Stochastic Optimization
;
Symbolic Systems
Abstract:
We present our observations regarding the emergent behaviour in a population of agents following a recently presented nature inspired resource allocation / scheduling method. By having agents distribute tasks among themselves based on their local view of the problem, we successfully balance the work across agents, while remaining flexible to adapt to dynamic scenarios where tasks are added, removed or modified. We explain the approach and within it the mechanisms that give rise to the emergent behaviour; we discuss the model used for the simulations, outline the algorithm and provide results illustrating the performance of the method.