Contract Net Protocol

About: Contract Net Protocol is a research topic. Over the lifetime, 606 publications have been published within this topic receiving 13729 citations.

Performance evaluation of an auction-based job allocation model for small- and medium-sized enterprises

Abstract: This paper extends the application scope of a previously developed auction-based shop floor control model to the enterprise level and evaluates its performance for the coordination and collaboration of spatially distributed Small- and Medium-sized Enterprises (SMEs). The model uses the contract net protocol to facilitate the negotiation process among SMEs and consists of two main components: task proposal formulation and bid formulation. An agent-based simulation environment is developed in ProModel to evaluate the impact of two negotiation factors and due date slack of tasks on tardiness, earliness and absolute due date deviation of tasks. A mixed-level factorial Design of Experiments (DOE) is carried out by considering different levels of α, β and K, and the results of the simulation study are analysed using Analysis of Variance (ANOVA) in Minitab. This study shows that the auction-based model is effective for the task allocation among SMEs, yet it is necessary to fine-tune the negotiation factors based on the due-date-related performance measures.

Multi-Agent based Information Warfare System Modeling and Simulation

Abstract: In this paper, multi-agent based modeling and simulation approach is used and multi-agent model of IWS is studied. In order to solve the problems about simulation of intelligent engagement action, dynamic information processing, and changing battlespace environment, we analyzed the problem space, battlespace and information processing of IWS, put forward the multi-agent organization of IWS and the architecture of agents. The cooperative control behavior model of combat principal combat is constructed, and the interaction mechanism and collaborative method of multiagent combat cooperative control are proposed and furthermore set up the elementary approach model of task decomposition and task allocation in this system, the Contract Net Protocol is used to task allocation of multi-agent IWS. The simulation result proves that the established distributed multiagent system model of IWS can afford advantage for carrying out the advanced concept technology demonstration of the external, dynamic, complicated and intelligent process.

Bottom-Up Mechanism and Improved Contract Net Protocol for Dynamic Task Planning of Heterogeneous Earth Observation Resources

Abstract: Earth observation resources are becoming increasingly indispensable in disaster relief, damage assessment, and other related domains. Many unpredictable factors, such as changes in observation task requirements, bad weather, and resource malfunctions, may cause the scheduled observation scheme to become infeasible. In these cases, it is crucial to promptly reformulate high-quality observation schemes while exerting minimal negative effects on the previously scheduled tasks. Accordingly, in this study, a bottom-up distributed coordination framework together with an improved contract net is proposed, aiming to facilitate dynamic task replanning for heterogeneous Earth observation resources. This hierarchical framework consists of three levels: 1) neighboring resource coordination; 2) single planning center coordination; and 3) multiple planning center coordination. The observation tasks affected by unpredicted factors are managed along with a bottom-up route from resources to planning centers. This bottom-up distributed coordination framework transfers part of the computing load to various nodes of the observation systems to plan tasks more efficiently and robustly. To support the prompt replanning of multiple 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 quickly obtain a promising replanning scheme. The simulation results demonstrate that the MCA method can achieve a better task completion rate for large-scale tasks with satisfactory time efficiency. In addition, this method can efficiently obtain replanning schemes based on original schemes in dynamic environments.

Aerial: A Framework to Support Human Decision Making in a Constrained Environment

Abstract: In this paper, we propose an architecture that uses a tender protocol, the Contract Net Protocol (CNP), to let human operators express their consent about the allocation of goals to Unmanned Aerial Vehicles (UAVs) in a constrained environment. The CNP has several good points: it has an appropriate level of automation, it is simple, it spares the bandwidth. But if bids are evaluated solely on the base of a numerical payoff, the CNP cannot fully convey human preference in complex situations. Thus, we extended and implemented the CNP within our framework, Aerial, to enable a more subjective human feedback. We detail how we build the bids and how we filter them to not flood the user. We also explain how we enable a dependable commitment in a dynamic context when the award time is not accurately foreseen.

Robot Heterogeneity Analysis Based on Extenics

Abstract: This paper presents a new method that robot heterogeneities are described by using an extension model based on Extenics, which is a new discipline and a new branch of artificial intelligence. Individual robot is the basic unit of a multi- robot system. The whole system's performance is determined by individual's capability. Heterogeneity determines a robot's difference in behavior and ability. Studying robot's heterogeneity is the foundation for the entire system to achieve the optimum state. This paper first analyses heterogeneous characters of robot generally, then an extension model is established to show heterogeneous characteristics. This extension model is used for task allocation which is based on contract net protocol. At the end, simulation is conducted in a multi-robot system. Simulation results validate this method.