Decision making of an agent depends on the other agents' behavior while sharing information is not always possible. On the other hand, predicting other agents' policies while they are also learning is a difficult task. Also, some agents in a multi-agent environment may not behave rationally. ...
这里s表示状态,ai表示agent i的动作,Qi表示agent i的动作价值函数,a1:i−1表示前序agent 1到i-1选择的动作序列。 ②反向依赖(Backward Dependency):更新一个agent的动作Q值时要依赖于后续agent对之前动作的反应。即更新agent i的动作Q值的target依赖于agent i+1到n对前序动作a1:i的最优反应: yi=r+γmaxai...
Multi-Agent Plan Recognition (MAPR) aims to recognize dynamic team structures and team behaviors from the observed team traces (activity sequences) of a set of intelligent agents. Previous MAPR approaches required a library of team activity sequences (team plans) be given as input. However, co...
They have had considerable success in single-agent domains and even in some multi-agent tasks. However, general multi-agent tasks often require mixed strategies whose distributions cannot be well approximated by Gaussians or their mixtures. This paper proposes an alternative for policy representation ...
其中第一个式子意为每一个 agent 要最大化他的个人利益,第二个式子表示为了实现 safe RL,每一步的 joint action 需要满足一些 constraints,注意到这里是 joint action 需要满足一些条件,这说明在安全性保证方面,不同 agent 的 action 是要有联动的。在实际算法中,我们通过 constrained optimization 来选择 action。
将得到的两个预训练任务的动作表征按一定的方式形成一个新的embedding,然后这个新的embedding指导agent执行另一个不同的任务。对于单模态任务集,比方说使用速度为1和2的HalfCheetah-Vel task,通过调整参数来合成这两个动作表征,来形成新的任务,比如说速度为1.2,1.5,1.8等,这些新任务在原始的任务集里面是没有的,...
Multi-agent systems (MASs) do play an important role in the construction of fault tolerant and robust robot systems. One major advantage of MAS is the fact that multiple agents work towards a common goal, having different skills for specific subtasks. Usually, agents have to use a common des...
For this, our model is based on multiagent system as well as on the affordance, emergence and stigmergy concepts (this paper emphasizes mainly the first two). 展开 关键词: Multiagent System Situated Action Affordance Emergence DOI: 10.5220/0005141606440651 ...
在执行一个 action 前,agent 检查(第 8 行)它是否对当前 state-action pair 在前一个模拟器 Σi-1 中的 transition function 有足够准确的估计(方差小于 σ_th)。 如果不是,并且如果当前环境中的 transition model 发生了变化,它就会切换到 Σi-1,并在 Σi-1 中执行 action 。 跟踪当前模拟器中,最近...
55-72. Springer.Carpenter, M., Kudenko, D.: Baselines for joint-action reinforcement learning of coordination in cooperative multi-agent systems. In: Kudenko, D., Kazakov, D., Alonso, E. (eds.) AAMAS 2004. LNCS, vol. 3394, pp. 55–72. Springer, Heidelberg (2005)...