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Showing papers on "Contract Net Protocol published in 2020"


Journal ArticleDOI
24 Apr 2020
TL;DR: A blockchain based TES is proposed that enables agents to receive incentives for providing voltage regulation services by maintaining an auditable reputation rating for each agent and utilizing smart contracts to enforce the validity of each transaction and penalize reputation ratings in case of a mitigation failure.
Abstract: Transactive energy systems (TES) are modern mechanisms in electric power systems that allow disparate control agents to utilise distributed generation units to engage in energy transactions and provide ancillary services to the grid. Although voltage regulation is a crucial ancillary grid service within active distribution networks (ADNs), previous work has not adequately explored how this service can be offered in terms of its incentivisation, contract auditability, and enforcement. Blockchain technology shows promise in being a key enabler of TES, allowing agents to engage in trustless, persistent transactions that are both enforceable and auditable. To that end, this study proposes a blockchain based TES that enables agents to receive incentives for providing voltage regulation services by (i) maintaining an auditable reputation rating for each agent that is increased proportionately with each mitigation of a voltage violation, (ii) utilising smart contracts to enforce the validity of each transaction and penalise reputation ratings in case of a mitigation failure, and (iii) automating the negotiation and bidding of agent services by implementing the contract net protocol as a smart contract. Experimental results on both simulated and real-world ADNs are executed to demonstrate the efficacy of the proposed system.

23 citations


Journal ArticleDOI
TL;DR: An efficient task offloading scheme based on improved contract net protocol and beetle antennae search algorithm is proposed and the analysis and simulation results validate the efficiency of the proposed scheme compared with other algorithms.
Abstract: For fog computing network, how to effectively and quickly offload the task to fog nodes is a big challenge. In this paper, a task offloading scheme based on improved contract net protocol and beetle antennae search algorithm in fog computing networks is proposed. Firstly, the system mode of task offloading in fog computing network is described. Then, a contract net protocol is presented to obtain the information from the fog nodes. Based on the information, the agent will allocate the sub-tasks to the fog nodes. And the task offloading issue in fog computing network is formulated and analyzed. Next, an efficient task offloading scheme based on improved contract net protocol and beetle antennae search algorithm is proposed. Finally, the analysis and simulation results validate the efficiency of the proposed scheme compared with other algorithms.

16 citations


Journal ArticleDOI
TL;DR: In this article, a single-task, single-robot, time-extended assignment problem with intra-schedule dependency using the multirobot task assignment taxonomy was formulated, and the sub-problem was solved by releasing urgent tasks in a mixed-integer linear programming model.

11 citations


Journal ArticleDOI
03 Oct 2020
TL;DR: In this paper, a contract net protocol (CNP) was applied for agent communication and interaction in a Flexible Manufacturing System (FMS) and a particular Algebraic Deadlock Avoidance Policy (DAP) was efficiently embedded into CNP.
Abstract: This work focuses on the efficient design of a controller for a Flexible Manufacturing System (FMS) using Agents. The necessary agents were selected and defined according to the Design of Agent-based Production Control Systems (DACS) methodology. The Contract Net Protocol (CNP) was applied for agent communication and interaction. A particular Algebraic Deadlock Avoidance Policy (DAP) is efficiently embedded into CNP. As a result the multi agent system is live and deadlock–free. Feasibility analysis of the controller was performed by exploiting Resource Allocation Systems techniques being defined in the framework of Petri Net theory. The controller is demonstrated in simulation mode in the framework of the Java Agent Development Framework (JADE) system

10 citations


Journal ArticleDOI
TL;DR: Experimental results show that D 2 S P performs at least equally or better than centralized and static SPs in terms of total profit, fairness, scalability, and communication overhead.

6 citations


10 Mar 2020
TL;DR: This paper analyzes the system of the ridesharing service of a French shared-mobility company, Mobicoop, revealing that indeed few older people utilize it and proposes a multi-agent systems (MAS) approach to build an innovative mobility service that older people will utilize.
Abstract: Technological and organizational innovations have promoted new modes of transport and services. Ridesharing has disrupted the entire transportation sector in the last decade, causing a cultural shift in the general population, but not so much in the older generations. In this paper, we propose a multi-agent systems (MAS) approach to build an innovative mobility service that older people will utilize. To do this, we analyze the system of the ridesharing service of a French shared-mobility company, Mobicoop, revealing that indeed few older people utilize it. In the context of the MobiPA project, we look into the reasons that are hindering this utilization. We propose using a continual innovation method, ADInnov, to better understand and innovate on Mobicoop's rideshar-ing ecosystem. Our proposal deals with each of the identified reasons by adopting MAS techniques and a socio-technical model. We describe the necessary concepts for modeling our multi-agent system, IMOPOP. In IMOPOP, we first use the Hodges' Health Career Model, originating from the social care domain, to model the actors in the ecosystem, further proposing it as an organizational innovation. Secondly, we employ the contract net protocol for the negotiation between agents for a ride contract. Finally, we use Agent-Oriented Programming for modeling time in the system.

5 citations


Posted ContentDOI
TL;DR: An agent- based simulation to investigate tasks allocation through the consideration of appropriate spatial strategies to deal with uncertainty in urban search and rescue (USAR) operation resulted in the optimization and increased flexibility of the allocation.
Abstract: . Task allocation in uncertainty conditions is a key problem for agents attempting to achieve harmony in disaster environments. This paper presents an agent- based simulation to investigate tasks allocation through the consideration of appropriate spatial strategies to deal with uncertainty in urban search and rescue (USAR) operation. The proposed method is presented in five phases: ordering existing tasks, finding coordinating agent, holding an auction, applying allocation strategies, and implementation and observation of environmental uncertainties. The methodology was evaluated in Tehran's District 1 for 6.6, 6.9, and 7.2 magnitude earthquakes. The simulation started by calculating the number of injured individuals, which was 28856, 73195 and 111463 people for each earthquake, respectively. The Simulations were performed for each scenario for a variety of rescuers (1000, 1500, 2000 rescuer). In comparison with contract net protocol (CNP), the standard time of rescue operations in the proposed approach includes at least 13% of improvement and the best percentage of recovery was 21 %. Interval uncertainty analysis and the comparison of the proposed strategies showed that an increase in uncertainty leads to an increased rescue time for CNP of 67.7 hours, and for strategies one to four an increased rescue time of 63.4, 63.2, 63.7, and 56.5 hours, respectively. Considering strategies in the task allocation process, especially spatial strategies, resulted in the optimization and increased flexibility of the allocation as well as conditions for fault tolerance and agent-based cooperation stability in USAR simulation system.

3 citations


Posted Content
13 Jul 2020
TL;DR: A multiround combinatorial allocation (MCA) method to support the prompt assignment of large-scale tasks to proper Earth observation resources in dynamic environments and a new float interval-based local search algorithm is proposed to obtain the promising planning scheme more quickly.
Abstract: Earth observation resources are becoming increasingly indispensable in disaster relief, damage assessment and related domains. Many unpredicted factors, such as the change of observation task requirements, to the occurring of bad weather and resource failures, may cause the scheduled observation scheme to become infeasible. Therefore, it is crucial to be able to promptly and maybe frequently develop high-quality replanned observation schemes that minimize the effects on the scheduled tasks. A bottom-up distributed coordinated framework together with an improved contract net are proposed to facilitate the dynamic task replanning for heterogeneous Earth observation resources. This hierarchical framework consists of three levels, namely, neighboring resource coordination, single planning center coordination, and multiple planning center coordination. Observation tasks affected by unpredicted factors are assigned and treated along with a bottom-up route from resources to planning centers. This bottom-up distributed coordinated framework transfers part of the computing load to various nodes of the observation systems to allocate tasks more efficiently and robustly. To support the prompt assignment of large-scale tasks to proper Earth observation resources in dynamic environments, we propose a multiround combinatorial allocation (MCA) method. Moreover, a new float interval-based local search algorithm is proposed to obtain the promising planning scheme more quickly. The experiments demonstrate that the MCA method can achieve a better task completion rate for large-scale tasks with satisfactory time efficiency. It also demonstrates that this method can help to efficiently obtain replanning schemes based on original scheme in dynamic environments.

2 citations


Proceedings ArticleDOI
09 Oct 2020
TL;DR: The simulation shows that the proposed assignment method of UAVs cooperative air-to-ground associated task based on MA-Contract Net Protocol can generate more reasonable assignment results for a variety of complex associated tasks and UAV fault situations, reduce the execution cost of associated tasks, and improve the task set completion degree and efficiency.
Abstract: Aiming at the problem of dynamic assignment of UAVs cooperative air-to-ground attacks based on associated tasks and fault mechanisms, an MA-based task executor and task publisher model was established, and an assignment method of UAVs cooperative air-to-ground associated task based on MA-Contract Net Protocol was proposed. The simulation shows that this method can generate more reasonable assignment results for a variety of complex associated tasks and UAV fault situations, reduce the execution cost of associated tasks, avoid the lack of task execution caused by UAV faults, and improve the task set completion degree and efficiency.

1 citations


Book ChapterDOI
08 Jun 2020
TL;DR: In this article, a prototype multi-agent-based system for cleaning food production facilities developed as part of the RoboClean project is described, which is based on domestic robot vacuum cleaners equipped with infrared allergen sensors and Amazon echo dot speech interfaces.
Abstract: In this paper, we describe a prototype multi-agent-based system for cleaning food production facilities developed as part of the RoboClean project. The prototype system is based on domestic robot vacuum cleaners equipped with infrared allergen sensors and Amazon echo dot speech interfaces. T.he robots are controlled by a multi-agent system implemented in Jason, which handles (ad hoc) task allocation and robot coordination. We briefly describe the architecture of the RoboClean system, how coordination is achieved using the contract net protocol, and the implementation of the current prototype.

1 citations


Proceedings ArticleDOI
01 Sep 2020
TL;DR: In this paper, the authors designed an architecture consisting of the Contract Net Protocol, the Behavior Tree, and a human-swarm interaction that was evaluated using team play in a simulated Tail Tag game.
Abstract: Despite the impressive advances in artificial intelligence (AI), close collaboration between people and AI systems is still hard to achieve. To overcome this problem, we have designed an architecture consisting of the Contract Net Protocol, the Behavior Tree, and a human–multiple agent interface that we call "human-swarm interaction." Its effectiveness and feasibility were evaluated using team play in a simulated Tail Tag game. Matches with up to 19 AI agents and 1 person on one team and 20 people on the other team were played. The results indicate that our system is scalable and that there is room for improvement. We identified two key features for AI agents to achieve collaboration with people in a serious game as represented by Tail Tag game: the ability to at least remain alive in any situation, and active declaration of roles being attempted as well as sharing of roles.

Patent
29 Sep 2020
TL;DR: In this paper, a collaborative method of a humanoid multi-robot consisting of determining task allocation mathematical model, describing a task allocation problem, and determining tasks, the robot capability and an objective function is presented.
Abstract: The invention provides a collaborative method of a humanoid multi-robot. The collaborative method comprises the following steps of determining a task allocation mathematical model, describing a task allocation problem, and determining tasks, the robot capability and an objective function; after describing the task allocation problem, defining a robot task sequence and formulating constraint conditions of the objective function; decomposing the tasks, establishing a hierarchical structure model of a robot system, and designing a behavior task tree of each robot on the basis of the hierarchicalstructure model; and completing the task allocation of distributed artificial intelligence through a negotiation mechanism of a contract net protocol CNP. Experimental verification shows that the method of the invention effectively improves the collaboration efficiency among multi-robot teams, shortens the running time of a multi-robot system, and has the effectiveness and robustness in solving practical and time-critical task allocation problems.

Book ChapterDOI
22 Feb 2020
TL;DR: In this article, the authors describe a distributed approach based on Multiagent Systems (MAS) to alleviate the dependency on a central node for material handling in the mining industry, where real-world equipment items such as shovels and trucks are represented by intelligent agents.
Abstract: Material handling is an important process in the mining industry because of its high operational cost. In this process, shovels extract and load materials that must be transported by trucks to different destinations at the mine. When a truck ends an unloading operation, it requires a new loading destination. If a centralized system provides destinations by following dispatching criteria, then one of the main disadvantages of this kind of systems is not being able to provide a precise dispatching solution without knowledge about potentially changed external conditions and the dependency on a central node. In this paper, we describe a distributed approach based on Multiagent Systems (MAS) to alleviate these disadvantages. In this approach, the real-world equipment items such as shovels and trucks are represented by intelligent agents. The agents interact with each other to generate schedules for the machines that they represent. For this interaction, a Contract Net Protocol with a confirmation stage was implemented. In addition, when a machine failure occurs, the agents are able to update their schedules. In order to evaluate the MAS, an agent-based simulation with data from a Chilean open-pit mine was used. The results show that the MAS is able to generate the schedules in a practical computation timeframe. The schedules generated by the MAS decrease the truck cost by 17% on average. Moreover, when a machine failure occurs, the agents are able to repair their schedules in a short period of time.

Patent
07 Aug 2020
TL;DR: In this article, a fog computing network task unloading method based on an improved contract net protocol and a beetle antennae search algorithm (BAS) is proposed to search for an optimal result.
Abstract: The invention discloses a fog computing network task unloading method based on an improved contract net protocol and a beetle antennae search algorithm (BAS). According to the method, firstly, an improved BAS algorithm combining a BAS and a genetic algorithm is proposed to search for an optimal result. The method comprises: firstly carrying out encoding and population initialization, then carryingout BAS process and updating, then carrying out beetle population propagation, and obtaining the optimal result after iteration is ended. In the fog computing network task unloading method, a task nodes publish tasks and collect bidding information in an agent or non-agent mode, operates the optimized algorithm to solve the optimization problem and obtain the optimal solution for executing the tasks, and finally divides the tasks into sub-tasks according to the optimal solution and distributes the tasks to the fog nodes. According to the fog computing network task unloading method based on the improved contract net protocol and the BAS, the tasks can be rapidly and effectively unloaded to the fog nodes, and the method is excellent in performance and easy to implement.

Proceedings ArticleDOI
21 Oct 2020
TL;DR: This work uses the extended version of the contract net protocol (ECNP) to optimize the movement of MASs inside a smart grid network, and demonstrates the efficiency and power of the ECNP, and the role of MAS in distributed management of smart grids.
Abstract: Smart grids are one of the best solutions for the integration of different distributed energy sources (DES), load, and storage elements. However, optimizing and managing these systems is a big challenge because it is only done in a distributed way. One of the best methods of managing a smart grid is the use of artificial intelligence (AI), especially multi-agent systems (MAS) approaches. MASs present a comprise of two or more independent agents with some information to achieve a set target that is capable of achieving multiple real-time objectives easily. Several multiagent approaches have been proposed these last years, This work constitutes a demonstration of one of those methods which is the contract net protocol (CNP). The CNP is a technique invented to solve communication problems in distributed networks. It was defined as a high-level protocol for communication among the nodes in distributed problem solver. We will use the extended version of the contract net protocol(ECNP) to optimize the movement of MASs inside a smart grid network. Our example of a smart grid will be a grid constituted from nodes, and each node is a location of a task or an agent. In the scenario each task it’s given a target which is also a node inside the grid, and our main objective is that the agent or agents could contribute for each task, depending on their priority order and may allow it to reach its target, which is another node in the network far from its initial location, using the shortest way as possible. A first scenario is used that includes a certain number of tasks and agents, to demonstrate the efficiency and power of the ECNP (extended contract net protocol), and the role of MAS in distributed management of smart grids.