We investigate the prevalence and learning impact of different types of off-task behavior in classrooms where students are using intelligent tutoring software. We find that within...
Ryan Shaun Baker, Albert T. Corbett, Kenneth R. Ko...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Multiagent learning literature has investigated iterated twoplayer games to develop mechanisms that allow agents to learn to converge on Nash Equilibrium strategy profiles. Such ...
In this paper, we present an evaluation of exaggerated headcoupled camera motions in a game-like 3D object movement. Three exaggeration levels were compared to determine if the ex...
We consider multi-agent systems whose agents compete for resources by striving to be in the minority group. The agents adapt to the environment by reinforcement learning of the pr...