Reinforcement Learning
"Reinforcement learning is learning what to do – how to map situations to actions – so as to maximize a numerical reward signal. The learner is not told which actions to take, as in most forms of machine learning, but instead must discover which actions yield the most reward by trying them."
– Sutton, Richard S. and Andrew G. Barto. Reinforcement Learning: An Introduction. (1.1). MIT Press, Cambridge, MA, 1998.
Multi-Agent Reinforcement Learning is A Sequence Modeling Problem
Neural Information Processing Systems
Our goal is to build the bridge between MARL and SMs so that the modeling power of modern sequence models can be unleashed for MARL.
Country:
Technology:
- Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (1.00)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Agents > Agent Societies (0.47)
Country:
- North America > Canada > Quebec > Montreal (0.04)
- Europe > Serbia > Central Serbia > Belgrade (0.04)
Technology:
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (0.69)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.69)
Country:
- Europe > United Kingdom > England > Oxfordshire > Oxford (0.14)
- Asia > Middle East > Jordan (0.04)
- Oceania > Australia (0.04)
- (3 more...)
Technology:
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Data Science (0.93)
- Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (0.73)
- (2 more...)
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and Planning
Neural Information Processing Systems
Model-based reinforcement learning algorithms with probabilistic dynamical models are amongst the most data-efficient learning methods.
Country:
- Europe > United Kingdom > England > Cambridgeshire > Cambridge (0.14)
- Asia (0.14)
- North America > United States > Massachusetts > Middlesex County (0.14)
- (3 more...)
Technology:
- Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.46)
Technology:
- Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (0.49)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Planning & Scheduling (0.37)
Country: North America > Canada > British Columbia > Metro Vancouver Regional District > Vancouver (0.04)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (1.00)
Technology:
- Information Technology > Artificial Intelligence > Representation & Reasoning > Agents (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (0.69)
- Information Technology > Artificial Intelligence > Robots (0.68)
main
Neural Information Processing Systems
The classical theory of reinforcement learning (RL) has focused on tabular and linear representations of value functions.
Country:
- Asia > Middle East > Jordan (0.04)
- North America > United States > California > Alameda County > Berkeley (0.04)
- North America > Canada (0.04)
- (2 more...)
Technology:
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning (0.94)
- Information Technology > Data Science > Data Mining (0.93)
Genre:
- Research Report > New Finding (0.47)
- Workflow (0.46)
Technology:
- Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (0.73)
- Information Technology > Artificial Intelligence > Natural Language > Explanation & Argumentation (0.68)
- Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models (0.68)
- Information Technology > Artificial Intelligence > Representation & Reasoning > Agents (0.46)
Country:
- North America > United States > Texas > Brazos County > College Station (0.04)
- North America > United States > Michigan (0.04)
- Asia > Thailand > Bangkok > Bangkok (0.04)
Technology:
- Information Technology > Artificial Intelligence > Representation & Reasoning (1.00)
- Information Technology > Artificial Intelligence > Machine Learning > Reinforcement Learning (0.95)
- Information Technology > Artificial Intelligence > Robots (0.78)
- Information Technology > Artificial Intelligence > Machine Learning > Learning Graphical Models (0.68)