DocumentCode :
3316799
Title :
Semantic shared space-based complex tasks allocation method for massive MAS
Author :
Brahmi, Zaki ; Gammoudi, Mohamed Mohsen
Author_Institution :
Res. Unit, URSIIVA, Tunisia
fYear :
2009
fDate :
8-11 Aug. 2009
Firstpage :
428
Lastpage :
434
Abstract :
Task allocation is still a fundamental problem in multi-agents system (MAS). It allows coalition formation of agents in order to cooperate together to perform a complex task. In general, the task allocation process includes two steps: i) finding the set of agents that can, potentially, participate to task allocation process, ii) computing the optimal allocation to execute the given task. In this work further attention is given for the first step. Indeed, in the context of massive MAS, characterized by dynamic, heterogeneous and a large number of autonomous agents, an efficient model of communication is required. This implies a need for a scalable and semantic infrastructure which allows: i) agents to be able to easily find each other and ii) semantic interoperability that refers to a common understanding of information communicated between agents. In this work information refers to an announced task. Different models of communication have been proposed, including broadcasting, forwarding, central server and group communication. Most of these approaches do not scale well in the context of massive MAS; when the number of agents grows. In additional, agent communication languages (ACLs), such as the KQML or FIPA ACL divide messages into several layers, and provide a specific syntax and semantics only for the outer layer, but its content is still arbitrary. To deal with these limitations, this paper extends our last task allocation method for massive MAS to shared space mechanism. This mechanism allows agents to find each by providing a logical shared space with temporal and special decoupling properties. To ensure semantic interoperability, we use a Task Ontology language (OWL-T) as a tuple space and a FIPA content message. OWL-T is based on the OWL for formally and semantically defining task in a high-level abstraction.
Keywords :
knowledge representation languages; multi-agent systems; ontologies (artificial intelligence); open systems; semantic Web; FIPA content message; OWL-T; autonomous agent communication language; massive MAS; multiagent system; semantic interoperability; semantic shared space-based complex optimal task allocation method; task ontology language; Autonomous agents; Broadcasting; Context modeling; Information analysis; Mechanical factors; Multiagent systems; OWL; Ontologies; Statistical analysis; Web services; Communication; Massive Multi-Agents System; OWL-T; Ontology; Shared space; Task Allocation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-4519-6
Electronic_ISBN :
978-1-4244-4520-2
Type :
conf
DOI :
10.1109/ICCSIT.2009.5234814
Filename :
5234814
Link To Document :
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