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» Control Knowledge to Improve Plan Quality
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AAAI
2004
14 years 11 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
15 years 3 months 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»
14 years 9 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
14 years 11 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
15 years 1 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