Essays about: "Exploration-Exploitation trade-off"
Found 5 essays containing the words Exploration-Exploitation trade-off.
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1. 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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2. Exploration-Exploitation Trade-off Approaches in Multi-Armed Bandit
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : Multi-armed bandit, a popular framework for sequential decision-making problems, has recently gained significant attention due to numerous applications. In Multi-armed Bandit, an agent faces the central challenge of choosing exploitation of its belief to hopefully gain a high reward and exploration to improve its knowledge of the environment, and any good strategy has to efficiently balance between the two actions. READ MORE
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3. A study of the exploration/exploitation trade-off in reinforcement learning : Applied to autonomous driving
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : A world initiative was set in motion for decreasing the amount of traffic accidents. Autonomous driving is a field which contributes to the initiative. Following report examines exploration/exploitationtrade-off in reinforcement learning applied to decision making in autonomous driving. READ MORE
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4. Minimal Exploration in Episodic Reinforcement Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Exploration-exploitation trade-off is a fundamental dilemma that reinforcement learning algorithms face. This dilemma is also central to the design of various state of the art bandit algorithms. We take inspiration from these algorithms and try to design reinforcement learning algorithms in an episodic setting. READ MORE
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5. On Bayesian optimization and its application to hyperparameter tuning
University essay from Linnéuniversitetet/Institutionen för matematik (MA)Abstract : This thesis introduces the concept of Bayesian optimization, primarly used in optimizing costly black-box functions. Besides theoretical treatment of the topic, the focus of the thesis is on two numerical experiments. READ MORE
