scholarly journals Advanced Double Layered Multi-Agent Systems Based on A3C in Real-Time Path Planning

Electronics ◽  
2021 ◽  
Vol 10 (22) ◽  
pp. 2762
Author(s):  
Dajeong Lee ◽  
Junoh Kim ◽  
Kyungeun Cho ◽  
Yunsick Sung
Keyword(s):  
State Space ◽  
Lower Layer ◽  
Goal Achievement ◽  
The State ◽  
Multi Agent Systems ◽  
Learning Time ◽  
Autonomous Surface Vehicle ◽  
Multi Agent ◽  
Vehicle Simulator ◽  
Time Required

In this paper, we propose an advanced double layered multi-agent system to reduce learning time, expressing a state space using a 2D grid. This system is based on asynchronous advantage actor-critic systems (A3C) and reduces the state space that agents need to consider by hierarchically expressing a 2D grid space and determining actions. Specifically, the state space is expressed in the upper and lower layers. Based on the learning results using A3C in the lower layer, the upper layer makes decisions without additional learning, and accordingly, the total learning time can be reduced. Our method was verified experimentally using a virtual autonomous surface vehicle simulator. It reduced the learning time required to reach a 90% goal achievement rate by 7.1% compared to the conventional double layered A3C. In addition, the goal achievement by the proposed method was 18.86% higher than that of the traditional double layered A3C over 20,000 learning episodes.

Dynamic Exploration of Multi-agent Systems with Periodic Timed Tasks

2020 ◽  
Author(s):  
Johan Arcile ◽  
Raymond Devillers ◽  
Hanna Klaudel
Keyword(s):  
State Space ◽  
Petri Net ◽  
Timed Automata ◽  
Autonomous Vehicle ◽  
Computation Time ◽  
The State ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Vehicle Systems ◽  
Multi Agent

We formalise and study multi-agent timed models MAPTs (Multi-Agent with Periodic timed Tasks), where each agent is associated with a regular timed schema upon which all possible actions of the agent rely. MAPTs allow for an accelerated semantics and a layered structure of the state space, so that it is possible to explore the latter dynamically and use heuristics to greatly reduce the computation time needed to address reachability problems. We use an available tool for the Petri net implementation of MAPTs, to explore the state space of autonomous vehicle systems. Then, we compare this exploration with timed automata-based approaches in terms of expressiveness of available queries and computation time.

Bounded Model Checking Algorithm to Reduce the State Space in Multi-Agent Systems

2014 ◽  
Vol 23 (11) ◽  
pp. 2835-2861
Author(s):  
Cong-Hua ZHOU ◽  
Meng YE ◽  
Chang-Da WANG ◽  
Zhi-Feng LIU
Keyword(s):  
Model Checking ◽  
State Space ◽  
Bounded Model Checking ◽  
The State ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent

Dynamic Exploration of Multi-agent Systems with Periodic Timed Tasks

2020 ◽  
Vol 175 (1-4) ◽  
pp. 59-95
Author(s):  
Johan Arcile ◽  
Raymond Devillers ◽  
Hanna Klaudel
Keyword(s):  
State Space ◽  
Petri Net ◽  
Timed Automata ◽  
Autonomous Vehicle ◽  
Computation Time ◽  
The State ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Vehicle Systems ◽  
Multi Agent

We formalise and study multi-agent timed models MAPTs (Multi-Agent with Periodic timed Tasks), where each agent is associated with a regular timed schema upon which all possible actions of the agent rely. MAPTs allow for an accelerated semantics and a layered structure of the state space, so that it is possible to explore the latter dynamically and use heuristics to greatly reduce the computation time needed to address reachability problems. We use an available tool for the Petri net implementation of MAPTs, to explore the state space of autonomous vehicle systems. Then, we compare this exploration with timed automata-based approaches in terms of expressiveness of available queries and computation time.

Set-Membership Filtering-Based Leader–Follower Synchronization of Discrete-Time Linear Multi-Agent Systems

2021 ◽  
Vol 143 (6) ◽  
Author(s):  
Diganta Bhattacharjee ◽  
Kamesh Subbarao
Keyword(s):  
Discrete Time ◽  
The State ◽  
Multi Agent Systems ◽  
State Estimator ◽  
Agent Systems ◽  
Set Membership ◽  
Multi Agent ◽  
Bounded Input ◽  
Time Linear ◽  
Synchronization Protocol

Abstract In this paper, a set-membership filtering-based leader–follower synchronization protocol for discrete-time linear multi-agent systems is proposed, wherein the aim is to make the agents synchronize with a leader. The agents, governed by identical high-order discrete-time linear dynamics, are subject to unknown-but-bounded input disturbances. In terms of its own state information, each agent only has access to measured outputs that are corrupted with unknown-but-bounded output disturbances. Also, the initial states of the agents are unknown. To deal with all these unknowns (or uncertainties), a set-membership filter (or state estimator), having the “correction-prediction” form of a standard Kalman filter, is formulated. We consider each agent to be equipped with this filter that estimates the state of the agent and consider the agents to be able to share the state estimate information with the neighbors locally. The corrected state estimates of the agents are utilized in the local control law design for synchronization. Under appropriate conditions, the global disagreement error between the agents and the leader is shown to be bounded. An upper bound on the norm of the global disagreement error is calculated and shown to be monotonically decreasing. Finally, a simulation example is included to illustrate the effectiveness of the proposed leader–follower synchronization protocol.

scholarly journals Nonlinear Convergence Algorithm: Structural Properties with Doubly Stochastic Quadratic Operators for Multi-Agent Systems

2018 ◽  
Vol 8 (1) ◽  
pp. 49-61 ◽  
Author(s):  
Rawad Abdulghafor ◽  
Sherzod Turaev ◽  
Akram Zeki ◽  
Adamu Abubaker
Keyword(s):  
Nonlinear Operator ◽  
Stochastic Matrices ◽  
Multi Agent Systems ◽  
Quadratic Operator ◽  
Dimensional Simplex ◽  
Agent Systems ◽  
Doubly Stochastic ◽  
Degroot Model ◽  
Multi Agent ◽  
Time Required

Abstract This paper proposes nonlinear operator of extreme doubly stochastic quadratic operator (EDSQO) for convergence algorithm aimed at solving consensus problem (CP) of discrete-time for multi-agent systems (MAS) on n-dimensional simplex. The first part undertakes systematic review of consensus problems. Convergence was generated via extreme doubly stochastic quadratic operators (EDSQOs) in the other part. However, this work was able to formulate convergence algorithms from doubly stochastic matrices, majorization theory, graph theory and stochastic analysis. We develop two algorithms: 1) the nonlinear algorithm of extreme doubly stochastic quadratic operator (NLAEDSQO) to generate all the convergent EDSQOs and 2) the nonlinear convergence algorithm (NLCA) of EDSQOs to investigate the optimal consensus for MAS. Experimental evaluation on convergent of EDSQOs yielded an optimal consensus for MAS. Comparative analysis with the convergence of EDSQOs and DeGroot model were carried out. The comparison was based on the complexity of operators, number of iterations to converge and the time required for convergences. This research proposed algorithm on convergence which is faster than the DeGroot linear model.

Consensus of heterogeneous linear multi-agent systems: Linear-transformation-based partial stability approach

2016 ◽  
Vol 39 (11) ◽  
pp. 1623-1630 ◽  
Author(s):  
Yangzhou Chen ◽  
Xiaojun Qu ◽  
A Yu Aleksandrov ◽  
Guiping Dai
Keyword(s):  
Linear Transformation ◽  
Analytical Formula ◽  
Design Procedure ◽  
The State ◽  
Consensus Problem ◽  
Multi Agent Systems ◽  
Consensus Protocol ◽  
Feedback Form ◽  
Partial Stability ◽  
Multi Agent

We deal with the state consensus problem of a general heterogeneous linear multi-agent system under a time-invariant and directed communication topology. First we adopt a general linear consensus protocol consisting of two parts. One is a state feedback of the agent for independently regulating its dynamics, and the other is a cooperative term in a generalized feedback form of the relative states between the agents. Then we propose a state-linear-transformation to equivalently transform the state consensus problem into a partial stability problem. Therefore, the result from the partial stability theory is applied to derive a sufficient and necessary algebraic criterion of consensus convergence, which is expressed in terms of the Hurwitz stability of a real matrix constructed from the parameters of both the agents’ models and the protocol. Meanwhile, an analytical formula of the consensus function is presented. Based on the criterion, we propose a design procedure of the gain matrices in the protocol by solving a bilinear matrix inequality.

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