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SYNASC
2006
IEEE
103views Algorithms» more  SYNASC 2006»
14 years 1 months ago
Incremental Deterministic Planning
We present a new planning algorithm that formulates the planning problem as a counting satisfiability problem in which the number of available solutions guides the planner determ...
Stefan Andrei, Wei-Ngan Chin, Martin C. Rinard
SOFSEM
2007
Springer
14 years 1 months ago
Incremental Learning of Planning Operators in Stochastic Domains
In this work we assume that there is an agent in an unknown environment (domain). This agent has some predefined actions and it can perceive its current state in the environment c...
Javad Safaei, Gholamreza Ghassem-Sani
ICRA
2003
IEEE
119views Robotics» more  ICRA 2003»
14 years 24 days ago
Incremental low-discrepancy lattice methods for motion planning
We present deterministic sequences for use in sampling-based approaches to motion planning. They simultaneously combine the qualities found in many other sequences: i) the increme...
Stephen R. Lindemann, Steven M. LaValle
IJRR
2010
114views more  IJRR 2010»
13 years 6 months ago
Generating Uniform Incremental Grids on SO(3) Using the Hopf Fibration
Abstract The problem of generating uniform deterministic samples over the rotation group, SO(3), is fundamental to many fields, such as computational structural biology, robotics,...
Anna Yershova, Swati Jain, Steven M. LaValle, Juli...
CI
2005
106views more  CI 2005»
13 years 7 months ago
Incremental Learning of Procedural Planning Knowledge in Challenging Environments
Autonomous agents that learn about their environment can be divided into two broad classes. One class of existing learners, reinforcement learners, typically employ weak learning ...
Douglas J. Pearson, John E. Laird