JAIR Article on Policy Learning
Wednesday, 04 July 2012 13:15
Dan
A paper on plan-based policy-learning has been published in Volume 44 of the Journal of Artificial Intelligence Research:
"Plan-based Policies for Efficient Multiple Battery Load Management" M. Fox, D. Long and D. Magazzeni Journal of Artificial Intelligence Research. 44. 2012. pp. 335–382
Click 'Read More' for the abstract.
Last Updated on Wednesday, 04 July 2012 13:17
Read more...
|
OPTIC: Optimising Preferences and Time-Dependent Costs
Thursday, 28 June 2012 13:47
Andrew Coles
OPTIC is a temporal planner for use in problems where plan cost is determined by preferences or time-dependent goal-collection costs. Such problems arise in a range of interesting situations, from scheduling the delivery of perishable goods, to coordinating order-fulfillment activities in warehouses.
Last Updated on Friday, 07 December 2012 13:40
Read more...
ECAI 2012
Wednesday, 23 May 2012 15:11
Andrew Coles
The group has had two conference papers accepted at ECAI 2012:
- Opportunistic Branched Plans to Maximise Utility in the Presence of Resource Uncertainty. A. J. Coles.
- Planning as Quantified Boolean Formula. M. Cashmore, M. Fox and E. Giunchiglia.
Last Updated on Friday, 25 May 2012 15:14
Automated Plan-Based Policy-Learning for Surveillance Problems (M. Fox, D. Long, A. I. Coles)
Friday, 01 June 2012 11:27
Andrew Coles
The group has successfully secured ESPRC funds (EP/J012157/1, fEC value £458,818) to research the use of planning to underpin policy learning for surveillance problems. Surveillance problems give rise to many challenges including the management of uncertainty in an unpredictable environment, the management of restricted resources and the communication of commitments and requests between multiple heterogeneous agent 'observers'. At the heart of surveillance problems lies the need to plan complex sequences of behaviour that achieve surveillance goals. These goals are typically expressed in terms of gathering as much information as possible given constraints, and communicating findings to a human operator.
Last Updated on Thursday, 06 September 2012 11:47
Read more...
|
JAIR Article on COLIN
Friday, 25 May 2012 16:12
Andrew Coles
A paper on COLIN, our flagship planner for problems with Continuous Linear Numeric Effects, has been published in Volu me 44 of the Journal of Artificial Intelligence Research:
"COLIN: Planning with Continuous Linear Numeric Change" A. J. Coles, A. I. Coles, M. Fox and D. Long Journal of Artificial Intelligence Research. 44. 2012. pp. 1–96
Click 'Read More' for the abstract.
Last Updated on Friday, 25 May 2012 15:20
Read more...
Bridging the Gap
Friday, 27 April 2012 15:16
Andrew Coles
Two pilot studies involving AI planning have been funded through the Interdisciplinary Informatics - Bridging the Gaps programme, working with researchers in Neuroimaging and Robotics. The projects explore the use of planning in novel application areas, continuing the group's recent work on planning for problems with time and numeric resources.
Last Updated on Friday, 27 April 2012 15:22
Read more...
Liner Shipping Fleet Repositioning
Monday, 20 February 2012 14:44
Andrew Coles
Situated at the heart of global trade, liner shipping networks transported over 1.3 billion tons of cargo on over 9,600 container vessels in 2011. Vessels are regularly repositioned between services in liner shipping networks to adjust the networks to the world economy and stay competitive. Since repositioning a single vessel can cost hundreds of thousands of US dollars, optimizing the repositioning activities of vessels is an important problem to the liner shipping industry.
Last Updated on Friday, 09 March 2012 10:58
Read more...
|
|
|
|
|
|
Page 1 of 3 |