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AIPS
2008
13 years 11 months ago
From One to Many: Planning for Loosely Coupled Multi-Agent Systems
Loosely coupled multi-agent systems are perceived as easier to plan for because they require less coordination between agent sub-plans. In this paper we set out to formalize this ...
Ronen I. Brafman, Carmel Domshlak
AIPS
2009
13 years 10 months ago
Learning User Plan Preferences Obfuscated by Feasibility Constraints
It has long been recognized that users can have complex preferences on plans. Non-intrusive learning of such preferences by observing the plans executed by the user is an attracti...
Nan Li, William Cushing, Subbarao Kambhampati, Sun...
JSW
2008
73views more  JSW 2008»
13 years 9 months ago
Teaching Virtual Experts for Multi-Domain Collaborative Planning
Abstract-- This paper presents an approach to rapid development of virtual planning experts that can collaborate to develop plans of action requiring expertise from multiple domain...
Gheorghe Tecuci, Mihai Boicu, Dorin Marcu, Marcel ...
AI
2000
Springer
13 years 8 months ago
Using temporal logics to express search control knowledge for planning
Over the years increasingly sophisticated planning algorithms have been developed. These have made for more efficient planners, but unfortunately these planners still suffer from ...
Fahiem Bacchus, Froduald Kabanza
ESWA
2011
243views Database» more  ESWA 2011»
13 years 12 days ago
A novel case based reasoning approach to radiotherapy planning
Radiotherapy planning is a complex problem which requires both expertise and experience of an oncologist. A Case Based Reasoning (CBR) system is developed to generate dose plans f...
Sanja Petrovic, Nishikant Mishra, Santhanam Sundar