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Showing result 1 - 5 of 92 essays matching the above criteria.
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1. Multi-Agent Deep Reinforcement Learning in Warehouse Environments
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This report presents a deep reinforcement algorithm for multi-agent systems based on the classicalDeep Q-Learning algorithm. The method considers a decentralized approach to controlling theagents, by equipping each agent with its own neural network and replay memory. READ MORE
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2. CoordinateFree Spacecraft Formation Control with Global Shape Convergence under VisionBased Sensing
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Formation control in multi-agent systems represents a groundbreaking intersection of various research fields with lots of emerging applications in various technologies. The realm of space exploration also can benefit significantly from formation control, facilitating a wide range of functions from astronomical observations, and climate monitoring to enhancing telecommunications, and on-orbit servicing and assembly. READ MORE
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3. Explainable AI for Multi-Agent Control Problem
University essay from Mälardalens universitet/Akademin för innovation, design och teknikAbstract : This report presents research on the application of policy explanation techniques in the context of coordinated reinforcement learning (CRL) for mobile network optimization. The goal was to improve the interpretability and comprehensibility of decision-making processes in multi-agent environments, with a particular focus on the Remote Antenna Tilt (RET) problem. READ MORE
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4. Distance-Based Formation Control, Maneuvering and Flip Ambiguity Avoidance in Multi-Agent Systems
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Formation control is a fundamental concept in the field of robotics, where a group ofagents is directed to achieve a specific formation or pattern. This report investigates decentralizeddistance-based formation control strategies for multiagent formation control, with a focus on controllaw design dealing with flip ambiguity issues, and centroid maneuvering. READ MORE
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5. Using Backward Chained Behavior Trees to Control Cooperative Minecraft Agents
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This report presents a strategy to control multiple collaborative intelligent agents acting in a complex, versatile environment. The proposed method utilizes back-chained behavior trees and 1-to-1 task distribution. The agents claim a task, which prevents other agents in the system to start working on the same task. READ MORE