Semantic shared space-based complez tasks allocation method for massive MAS
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.
Task Allocation Massive Multi-Agents System Communication Shared space Ontology OWL-T
Zaki Brahmi Mohamed Mohsen Gammoudi
URSIIVA Research Unit Tunisia High School of Statistics and Information Analysis of Tunis Tunisia
国际会议
北京
英文
1089-1095
2009-08-08（万方平台首次上网日期，不代表论文的发表时间）