Abstract: This paper investigates reinforcement learning algorithms for discrete-time stochastic multi-agent graphical games with multiplicative noise. The Bellman optimality equation for stochastic ...

In the 1980s, Andrew Barto and Rich Sutton were considered eccentric devotees to an elegant but ultimately doomed idea—having machines learn, as humans and animals do, from experience. Decades on, ...

两天快速复习完了强化学习，接下来准备直接看篇CMA论文(Reinforced Cross-Modal Matching and Self-Supervised Imitation Learning for Vision-Language ...

Abstract: Reinforcement learning (RL) has been widely used in recent years to solve combinatorial optimization problems; however, it has some limitations when solving such problems with practical ...

Notebook that demonstrates fundamentals of reinforcement learning: Policy Evaluation and Policy Improvement, Value and Policy Iteration, Bellman Equations. For more information please check out the ...

ChatGPT and other AI tools are upending our digital lives, but our AI interactions are about to get physical. Humanoid robots trained with a particular type of AI to sense and react to their world ...

The use of pessimism, when reasoning about datasets lacking exhaustive exploration has recently gained prominence in offline reinforcement learning. Despite the robustness it adds to the algorithm, ...