Sciweavers

Share
AIPS
2007

Concurrent Probabilistic Temporal Planning with Policy-Gradients

11 years 10 months ago
Concurrent Probabilistic Temporal Planning with Policy-Gradients
We present an any-time concurrent probabilistic temporal planner that includes continuous and discrete uncertainties and metric functions. Our approach is a direct policy search that attempts to optimise a parameterised policy using gradient ascent. Low memory use, plus the use of function approximation methods, plus factorisation of the policy, allow us to scale to challenging domains. This Factored Policy Gradient (FPG) Planner also attempts to optimise both steps to goal and the probability of success. We compare the FPG planner to other planners on CPTP domains, and on simpler but better studied probabilistic non-temporal domains.
Douglas Aberdeen, Olivier Buffet
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2007
Where AIPS
Authors Douglas Aberdeen, Olivier Buffet
Comments (0)
books