Nine rock types including Sandstone, Limestone, Siltstone, Dolomite and Marl collected from six different rock formations of the Salt Range area of Pakistan were tested to evaluate the correlations between the uniaxial compressive strength and the corresponding values of the point load index. Two hundred rock cores were drilled and used for the uniaxial compressive strength and point load index...

Route choice is an important stage in transport planning and modeling. Most of the existing approaches do not consider that road users can nowadays consult new technologies to plan their routes. In this paper, we combine multi-agent reinforcement learning (MARL) and car-to-infrastructure communication (C2I) to deal with route choice. The agents (road users) and the infrastructure interact with ...

A recent study of the Minnesota Agriculture and Rural Leadership (MARL) program set out to determine the relationship between andragogical program design and increased levels of emotional intelligence (EI). Members of two cohorts in the MARL leadership development program received different levels of focused effort, peer coaching, individual action plans, disorienting dilemmas, self-reflection,...

Role-based learning is a promising approach to improving the performance of Multi-Agent Reinforcement Learning (MARL). Nevertheless, without manual assistance, current role-based methods cannot guarantee stably discovering set roles effectively decompose complex task, as they assume either predefined role structure or practical experience for selecting hyperparameters. In this article, we propo...

Abstract Reinforcement Learning (RL) has emerged as a powerful tool to solve sequential decision-making problems, where learning agent interacts with an unknown environment in order maximize its rewards. Although most RL real-world applications involve multiple agents, the Multi-Agent (MARL) framework is still poorly understood from theoretical point of view. In this manuscript, we take step to...

Despite the increasing interest in multiagent reinforcement learning (MARL) multiple communities, understanding its theoretical foundation has long been recognized as a challenging problem. In this article, we address problem by providing finite-sample analysis for decentralized batch MARL. Specifically, consider type of mixed MARL setting with both cooperative and competitive agents, where two...