基于高效拍卖的分布式多智能体规划协调
1 任务拍卖与规划基础
在分布式多智能体规划中,拍卖是一种有效的任务分配方式。拍卖师在整个过程中起着核心作用,它会发布任务相关信息,智能体则进行投标。智能体的投标包含任务计划以及两个时间戳,分别表示开始和完成任务的时间,这有助于拍卖师决定任务分配。
拍卖师的工作流程如下:
Algorithm 2. Auctioneer: abstract plan and offering sub-tasks
1: state ←stateinit, Events ←∅, Proposed ←∅, plancomb ←∅
2: while ⊤do
3:
planabs ←make abstract plan(state, Events)
▷Call PDDL planner
4:
if |planabs| = 0 then
5:
return plancomb
6:
end if
7:
Actionsenv, Tasks ←determine executable prefix(planabs)
8:
state, plancomb ←apply(Actionsenv)
9:
Events ←extract events(plancomb)
10:
offer tasks and wait(Assignments, Events, Tasks)
▷Send to agents
11:
Proposals ←receive()
▷Receive from agents
12:
Assignment
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