Abstract
Planning and distributed task allocation are considered challenging problems. To address them, autonomous agents called planning agents situated in a multi-agent system should cooperate to achieve planning and complete distributed tasks. We propose a solution for distributed task allocation where agents dynamically allocate the tasks while they are building the plans. We model and verify some properties using computation tree logic (CTL) with the model checker its-ctl. Lastly, simulations are performed to verify the effectiveness of our proposed solution. The result proves that it is very efficient as it requires little message exchange and computational time. A benchmark production system is used as a running example to explain our contribution.
Highlights
Distributed artificial intelligence (DAI) is classified under two umbrellas: the distributed system and the multi-agent system (MAS)
We determine the distributed task allocation applied by planning agents
To evaluate our proposed solution for distributed task allocation in a multi-agent system, we test its efficiency compared with a second approach [37] and the greedy distributed allocation protocol (GDAP) [38]
Summary
Distributed artificial intelligence (DAI) is classified under two umbrellas: the distributed system and the multi-agent system (MAS). The multi-agent system is considered very important as it combines artificial intelligence with the distributed system [9,10,11]. To ensure cooperation between agents in a multi-agent system, planning is needed, which leads to more complications. We distinguish the following five phases to establish multi-agent planning:. Agent-based planning is considered as a single agent task [21,22,23]. We consider a multi-agent cooperation system based on planning and distributed task allocation, which is based on the following steps: (1) agent-based planning, (2) formal specification and verification, and (3) evaluation. We determine the distributed task allocation applied by planning agents.
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