3 resultados para Multi-agent simulation and artificial snow optimization


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In a team of multiple agents, the pursuance of a common goal is a defining characteristic. Since agents may have different capabilities, and effects of actions may be uncertain, a common goal can generally only be achieved through a careful cooperation between the different agents. In this work, we propose a novel two-stage planner that combines online planning at both team level and individual level through a subgoal delegation scheme. The proposal brings the advantages of online planning approaches to the multi-agent setting. A number of modifications are made to a classical UCT approximate algorithm to (i) adapt it to the application domains considered, (ii) reduce the branching factor in the underlying search process, and (iii) effectively manage uncertain information of action effects by using information fusion mechanisms. The proposed online multi-agent planner reduces the cost of planning and decreases the temporal cost of reaching a goal, while significantly increasing the chance of success of achieving the common goal. 

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Experimental tests have been completed for high-strength 8.8 bolts for studying their mechanical performance subjected to tensile loading. As observed from these tests, failure of structural bolts has been identified as in one of two ways: threads stripping and necking of the threaded portion of the bolt shank, which is possibly due to the degree of fit between internal and external threads. Following the experimental work, a numerical approach has been developed for demonstration of the tensile performance with proper consideration of tolerance class between bolts and nuts. The degree of fit between internal and external threads has been identified as a critical factor affecting failure mechanisms of high-strength structural bolts in tension, which is caused by the machining process. In addition, different constitutive material laws have been taken into account in the numerical simulation, demonstrating the entire failure mechanism for structural bolts with different tolerance classes in their threads. It is also observed that the bolt capacities are closely associated with their failure mechanisms.

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Planning is an essential process in teams of multiple agents pursuing a common goal. When the effects of actions undertaken by agents are uncertain, evaluating the potential risk of such actions alongside their utility might lead to more rational decisions upon planning. This challenge has been recently tackled for single agent settings, yet domains with multiple agents that present diverse viewpoints towards risk still necessitate comprehensive decision making mechanisms that balance the utility and risk of actions. In this work, we propose a novel collaborative multi-agent planning framework that integrates (i) a team-level online planner under uncertainty that extends the classical UCT approximate algorithm, and (ii) a preference modeling and multicriteria group decision making approach that allows agents to find accepted and rational solutions for planning problems, predicated on the attitude each agent adopts towards risk. When utilised in risk-pervaded scenarios, the proposed framework can reduce the cost of reaching the common goal sought and increase effectiveness, before making collective decisions by appropriately balancing risk and utility of actions.