نتایج جستجو برای: multi period systems
تعداد نتایج: 2010234 فیلتر نتایج به سال:
this paper deals with leader-following and leaderless consensus problems of high-order multi-input/multi-output (mimo) multi-agent systems with unknown nonlinear dynamics in the presence of uncertain external disturbances. the agents may have different dynamics and communicate together under a directed graph. a distributed adaptive method is designed for both cases. the structures of the contro...
The current paper develops three different ways to measure the multi-period global cost efficiency for homogeneous networks of processes when the prices of exogenous inputs are known at all time periods. A multi-period network data envelopment analysis model is presented to measure the minimum cost of the network system based on the global production possibility set. We show that there is a rel...
the environmental rules of reverse logistic networks have caused important economic growth in the past decades. to integrate forward logistic networks with reverse logistics networks a helpful method is to design both networks simultaneously. considering more retrieval choices in modeling reverse logistic systems can be very critical. this article contains a mixed integer linear programming mod...
multi agent markov decision processes (mmdps), as the generalization of markov decision processes to the multi agent case, have long been used for modeling multi agent system and are used as a suitable framework for multi agent reinforcement learning. in this paper, a generalized learning automata based algorithm for finding optimal policies in mmdp is proposed. in the proposed algorithm, mmdp ...
optimal adaptive leader-follower consensus of linear multi-agent systems: known and unknown dynamics
in this paper, the optimal adaptive leader-follower consensus of linear continuous time multi-agent systems is considered. the error dynamics of each player depends on its neighbors’ information. detailed analysis of online optimal leader-follower consensus under known and unknown dynamics is presented. the introduced reinforcement learning-based algorithms learn online the approximate solution...
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