Now showing items 1-10 of 15
Planning and Doing Things
(AISB Quarterly, 2007)
I was interested in computers by the age of 15 and gave talks on them at school. I attended evening classes a couple of years later while still at school travelling on the bus for an hour in the evening to a college in ...
Supporting Collaborative Operations within a Coalition Personnel Recovery Center
(Institute of Electrical and Electronics Engineers (IEEE), 2007-05)
Abstract—I-X is a framework that can be used to create an application in which multiple agents adopt a task-centric view of a situation, and which supports the necessary coordination of their activities to respond to that ...
Cooperating Reasoning Processes: More than Just the Sum of their Parts
(IJCAI Inc, 2007-01-06)
Collaborative Operations for Personnel Recovery Final Report on DARPA/AFRL
(Artificial Intelligence Applications Institute, 2007-08-31)
The Collaborative Operations for Personnel Recovery (Co-OPR) project sought to provide collaborative task support for a Search and Rescue coordination center. The project aimed to create a prototype “Personnel Recovery ...
Robustness of VOR and OKR adaptation under kinematics and dynamics transformations
Many computational models of vestibulo-ocular reflex (VOR) adaptation have been proposed, however none of these models have explicitly highlighted the distinction between adaptation to dynamics transformations, in which ...
Structure Inference for Bayesian Multisensory Perception and Tracking
We investigate a solution to the problem of multisensor perception and tracking by formulating it in the framework of Bayesian model selection. Humans robustly associate multi-sensory data as appropriate, but previous ...
Reconstructing Null-space Policies Subject to Dynamic Task Constraints in Redundant Manipulators
We consider the problem of direct policy learning in situations where the policies are only observable through their projections into the null-space of a set of dynamic, non-linear task constraints. We tackle the issue ...
Value Function Approximation on Non-Linear Manifolds for Robot Motor Control
The least squares approach works efficiently in value function approximation, given appropriate basis functions. Because of its smoothness, the Gaussian kernel is a popular and useful choice as a basis function. However, ...
Linear and Nonlinear Generative Probabilistic Class Models for Shape Contours
We introduce a robust probabilistic approach to modeling shape contours based on a low- dimensional, nonlinear latent variable model. In contrast to existing techniques that use objective functions in data space without ...