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» Control Knowledge to Improve Plan Quality
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AAAI
2004
13 years 9 months ago
Low-Knowledge Algorithm Control
This paper addresses the question of allocating computational resources among a set of algorithms in order to achieve the best performance on a scheduling problem instance. Our pr...
Tom Carchrae, J. Christopher Beck
ICCBR
2005
Springer
14 years 29 days ago
Case Adaptation by Segment Replanning for Case-Based Planning Systems
An adaptation phase is crucial for a good and reasonable Case-Based Planning (CBP) system. The adaptation phase is responsible for finding a solution in order to solve a new proble...
Flavio Tonidandel, Marcio Rillo
JVCIR
2006
140views more  JVCIR 2006»
13 years 7 months ago
Improved H.264 rate control by enhanced MAD-based frame complexity prediction
This paper presents a revised rate control scheme based on an improved frame complexity measure. Rate control adopted by both MPEG-4 VM18 and H.264/AVC use a quadratic rate-distor...
Xiaoquan Yi, Nam Ling
AAAI
1994
13 years 8 months ago
Control Strategies for a Stochastic Planner
We present new algorithms for local planning over Markov decision processes. The base-level algorithm possesses several interesting features for control of computation, based on s...
Jonathan Tash, Stuart J. Russell
EPS
1998
Springer
13 years 11 months ago
Evolving Heuristics for Planning
Abstract. In this paper we describe EvoCK, a new approach to the application of genetic programming (GP) to planning. This approach starts with a traditional AI planner (PRODIGY)an...
Ricardo Aler, Daniel Borrajo, Pedro Isasi