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» Intelligent exploration method for XCS
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GECCO
2005
Springer
13 years 10 months ago
Intelligent exploration method for XCS
Exploration/Exploitation equilibrium is one of the most challenging issues in reinforcement learning area as well as learning classifier systems such as XCS. In this paper1 , an i...
Ali Hamzeh, Adel Rahmani
GECCO
2007
Springer
228views Optimization» more  GECCO 2007»
13 years 11 months ago
Collective behavior based hierarchical XCS
This paper attempts to extend the XCS research by analyzing the impact of information exchange between XCS agents on classifier performance. Two types of information are exchange...
Matthew Gershoff, Sonia Schulenburg
CEC
2005
IEEE
13 years 6 months ago
XCS with computed prediction in continuous multistep environments
We apply XCS with computed prediction (XCSF) to tackle multistep reinforcement learning problems involving continuous inputs. In essence we use XCSF as a method of generalized rein...
Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wils...
GECCO
2006
Springer
128views Optimization» more  GECCO 2006»
13 years 8 months ago
FTXI: fault tolerance XCS in integer
In the realm of data mining, several key issues exists in the traditional classification algorithms, such as low readability, large rule number, and low accuracy with information ...
Hong-Wei Chen, Ying-Ping Chen
GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
13 years 8 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson