73 search results - page 7 / 15 » Incremental Learning of Planning Operators in Stochastic Dom... |
ECP
1997
Springer
13 years 11 months ago
1997
Springer
In this paper we describe SINERGY, which is a highly parallelizable, linear planning system that is based on the genetic programming paradigm. Rather than reasoning about the world...
CPAIOR
2006
Springer
13 years 11 months ago
2006
Springer
Temporal planning (TP) is notoriously difficult because it requires to solve a propositional STRIPS planning problem with temporal constraints. In this paper, we propose an efficie...
AGENTS
1998
Springer
13 years 11 months ago
1998
Springer
Physical domains are notoriously hard to model completely and correctly, especially to capture the dynamics of the environment. Moreover, since environments change, it is even mor...
NIPS
2003
13 years 8 months ago
2003
We study an approach to policy selection for large relational Markov Decision Processes (MDPs). We consider a variant of approximate policy iteration (API) that replaces the usual...
AIPS
2008
13 years 9 months ago
2008
As no plan can cover all possible contingencies, the ability to detect failures during plan execution is crucial to the robustness of any autonomous system operating in a dynamic ...