Sciweavers

1359 search results - page 242 / 272
» Neural Dynamics with Stochasticity
Sort
View
UAI
2003
14 years 9 days ago
Learning Continuous Time Bayesian Networks
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
Uri Nodelman, Christian R. Shelton, Daphne Koller
AAAI
1994
14 years 8 days ago
Learning to Coordinate without Sharing Information
Researchers in the eld of Distributed Arti cial Intelligence (DAI) have been developing e cient mechanisms to coordinate the activities of multiple autonomous agents. The need for...
Sandip Sen, Mahendra Sekaran, John Hale
ATAL
2010
Springer
14 years 1 days ago
Joint process games: from ratings to wikis
We introduce a game setting called a joint process, where the history of actions determine the state, and the state and agent properties determine the payoff. This setting is a sp...
Michael Munie, Yoav Shoham
ANOR
2007
73views more  ANOR 2007»
13 years 11 months ago
A sample-path approach to optimal position liquidation
We consider the problem of optimal position liquidation with the aim of maximizing the expected cash flow stream from the transaction in the presence of temporary or permanent ma...
Pavlo A. Krokhmal, Stan Uryasev
AUTOMATICA
2007
124views more  AUTOMATICA 2007»
13 years 11 months ago
Motion planning in uncertain environments with vision-like sensors
In this work we present a methodology for intelligent path planning in an uncertain environment using vision like sensors, i.e., sensors that allow the sensing of the environment ...
Suman Chakravorty, John L. Junkins