In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
— This paper presents a new reinforcement learning algorithm for accelerating acquisition of new skills by real mobile robots, without requiring simulation. It speeds up Q-learni...
While existing learning techniques can be viewed as inducing programs from examples, most research has focused on rather narrow classes of programs, e.g., decision trees or logic ...
We propose a method for learning models of people’s motion behaviors in an indoor environment. As people move through their environments, they do not move randomly. Instead, the...
An agent must acquire internal representation appropriate for its task, environment, sensors. As a learning algorithm, reinforcement learning is often utilized to acquire the rela...