Essays about: "reinforcement strategies"
Showing result 1 - 5 of 66 essays containing the words reinforcement strategies.
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1. The Effect of Chloride-Induced Corrosion Patterns on the Crack Width of Reinforced Concrete
University essay from KTH/BetongbyggnadAbstract : This master's thesis investigates cracking in a parking garage, with a particular focus on the influence of corrosion. Concrete structures commonly experience cracking, and corrosion has emerged as one of the primary contributing factors. These cracks, varying in size and shape, can be considered structural discontinuities. READ MORE
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2. Reinforcement Learning for Multi-Agent Strategy Synthesis Using Higher-Order Knowledge
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Imagine for a moment we are living in the distant future where autonomous robots are patrollingthe streets as police officers. Two such robots are chasing a robber through the city streets. Fearingthe thief might listen in to any potential transmission, both robots remain radio silent and are thuslimited to a strictly visual pursuit. READ MORE
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3. The Self-improvement Project : A theoretical analysis on self-discipline & hegemonic masculinity
University essay from Örebro universitet/Institutionen för humaniora, utbildnings- och samhällsvetenskapAbstract : While the idea of self-help has historically been associated with women the growing popularity of online self-improvement groups has attracted both sexes. The growing popularity of people like Jordan Peterson and Andrew Tate - who speak of the importance of self-improvement alongside anti-feminist rhetoric - within the Manosphere online community also shows a trend of self-improvement moving towards a male audience. READ MORE
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4. S-MARL: An Algorithm for Single-To-Multi-Agent Reinforcement Learning : Case Study: Formula 1 Race Strategies
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : A Multi-Agent System is a group of autonomous, intelligent, interacting agents sharing an environment that they observe through sensors, and upon which they act with actuators. The behaviors of these agents can be either defined upfront by programmers or learned by trial-and-error resorting to Reinforcement Learning. READ MORE
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5. Optimal Gait Control of Soft Quadruped Robot by Model-based Reinforcement Learning
University essay from KTH/Skolan för industriell teknik och management (ITM)Abstract : Quadruped robots offer distinct advantages in navigating challenging terrains due to their flexible and shock-absorbing characteristics. This flexibility allows them to adapt to uneven surfaces, enhancing their maneuverability. READ MORE