Definition
In reinforcement learning, intrinsic motivation drives an agent to explore its environment by seeking novelty, reducing uncertainty, or mastering skills, independent of extrinsic task rewards. This mechanism helps solve the sparse reward problem by providing dense internal feedback signals. By encouraging exploration, intrinsic motivation allows agents to discover useful behaviors and states that might otherwise remain unvisited, leading to more robust and generalizable policies in complex environments.
Summary
A reinforcement learning concept where agents pursue goals based on internal curiosity or knowledge acquisition rather than external rewards.
Key Concepts
- Reinforcement Learning
- Exploration vs Exploitation
- Curiosity-driven learning
- Sparse rewards
Use Cases
- Robotics navigation in unknown terrains
- Game playing agents discovering strategies
- Autonomous vehicle training