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...
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...
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...
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 ...
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