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Reinforcement learning: An overview
K Murphy - ar** and
challenging area in embodied AI. It is crucial for advancing next-generation intelligent robots …
challenging area in embodied AI. It is crucial for advancing next-generation intelligent robots …
Using Diffusion Models as Generative Replay in Continual Federated Learning--What will Happen?
Federated learning (FL) has become a cornerstone in decentralized learning, where, in
many scenarios, the incoming data distribution will change dynamically over time …
many scenarios, the incoming data distribution will change dynamically over time …
Using Variational Autoencoders to Generate 4D Synthetic Flight Tracks for Collision Risk Safety Analysis
Approval of new airspace procedures and/or technologies requires the evaluation of the
probability of air-to-air collisions against a Target Level of Safety (eg 10E-9) using Collision …
probability of air-to-air collisions against a Target Level of Safety (eg 10E-9) using Collision …
Bayes Adaptive Monte Carlo Tree Search for Offline Model-based Reinforcement Learning
Offline reinforcement learning (RL) is a powerful approach for data-driven decision-making
and control. Compared to model-free methods, offline model-based reinforcement learning …
and control. Compared to model-free methods, offline model-based reinforcement learning …
Dynamic Obstacle Avoidance through Uncertainty-Based Adaptive Planning with Diffusion
By framing reinforcement learning as a sequence modeling problem, recent work has
enabled the use of generative models, such as diffusion models, for planning. While these …
enabled the use of generative models, such as diffusion models, for planning. While these …
Decision-Making via Optimization in Challenging Environment: Bayesian and Multi-Agent Reinforcement Learning Perspectives
Y Mei - 2025 - search.proquest.com
Decision-making is essential in many real-world problems, where the goal is to select
actions that optimize long-term outcomes under uncertainty. From tuning hyperparameters to …
actions that optimize long-term outcomes under uncertainty. From tuning hyperparameters to …
Effective Value Function Factorization and Exploration in Multi-Agent Reinforcement Learning
H Zhou - 2024 - search.proquest.com
The evolution of computer science has profoundly impacted decision-making processes
across diverse domains, culminating in the development of artificial intelligence (AI) and …
across diverse domains, culminating in the development of artificial intelligence (AI) and …