: Massively Multiplayer Online Games (MMOGs) are increasing in both popularity and scale, and while classical Client/Server architectures convey some benefits, they suffer from s...
Classically, an approach to the multiagent policy learning supposed that the agents, via interactions and/or by using preliminary knowledge about the reward functions of all playe...
We apply CMA-ES, an evolution strategy with covariance matrix adaptation, and TDL (Temporal Difference Learning) to reinforcement learning tasks. In both cases these algorithms se...
The parametrization of business games benefits from the usage of a multi-tier architecture and software services. This paper shows that the multi-tier concept supports parametriz...
How to adaptively choose optimal neighborhoods is very important to pixel-domain image denoising algorithms since too many neighborhoods may cause over-smooth artifacts and too fe...