An important issue in reinforcement learning is how to incorporate expert knowledge in a principled manner, especially as we scale up to real-world tasks. In this paper, we presen...
Eric Wiewiora, Garrison W. Cottrell, Charles Elkan
We present a general methodology to automate the search for equilibrium strategies in games derived from computational experimentation. Our approach interleaves empirical game-the...
Reinforcement Learning is a commonly used technique in robotics, however, traditional algorithms are unable to handle large amounts of data coming from the robot’s sensors, requi...
– This paper describes two experiments with supervised reinforcement learning (RL) on a real, mobile robot. Two types of experiments were preformed. One tests the robot’s relia...
The execution order of a block of computer instructions on a pipelined machine can make a difference in running time by a factor of two or more. Compilers use heuristic schedulers...