Guest Post By Thecoinrepublic.com: Reinforcement Learning: Empowering Artificial Intelligence

Reinforcement learning (RL) is a crucial method within artificial intelligence, allowing software agents to independently acquire optimal behavior by engaging in a process of trial and error with their surroundings. RL is well-suited for tackling real-world sequential decision-making problems, especially involving control and robotics, and has become an active research area in the fields of AI and machine-learning. The foundations of reinforcement learning stem from diverse fields, including behavioral psychology, control theory, operations research, neuroscience, and statistics. Key concepts that form the theoretical bedrock of reinforcement learning include Markov decision processes, dynamic programming, temporal difference learning, and multi-armed bandits.