We introduce relational temporal difference learning as an effective approach to solving multi-agent Markov decision problems with large state spaces. Our algorithm uses temporal ...
We present a novel Bayesian approach to the problem of value function estimation in continuous state spaces. We define a probabilistic generative model for the value function by i...
Many real life datasets have skewed distributions of events when the probability of observing few events far exceeds the others. In this paper, we observed that in skewed datasets...
In this paper, we introduce WPML (WebProfiles Markup Language) for expressing user-context preferences information in the Web. Using WPML a service provider can negotiate and obta...
Despite many sensor, hardware, networking, and software advances, it is still quite difficult to build effective and reliable context-aware applications. We propose to build a con...