Results 1 - 10 of 489

Classifier fitness based on accuracy

by Stewart W. Wilson - Evolutionary Computation , 1995
"... In many classifier systems, the classifier strength parameter serves as a predictor of future payoff and as the classifier’s fitness for the genetic algorithm. We investigate a classifier system, XCS, in which each classifier maintains a prediction of expected payoff, but the classifier’s fitness is ..."
Abstract - Cited by 350 (17 self) - Add to MetaCart
is given by a measure of the prediction’s accuracy. The system executes the genetic algorithm in niches defined by the match sets, instead of panmictically. These aspects of XCS result in its population tending to form a complete and accurate mapping X x A + P from inputs and actions to payoff predictions

XCS for Adaptive User-Interfaces

by Anil Shankar, Sushil J. Louis, Ramona Houmanfar, Linda J. Hayes, Sergiu Dascalu
"... We outline our context learning framework that harnesses information from a user’s environment to learn user preferences for application actions. Within this framework, we employ XCS in a real world application for personalizing user-interface actions to individual users. Sycophant, our context awar ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
We outline our context learning framework that harnesses information from a user’s environment to learn user preferences for application actions. Within this framework, we employ XCS in a real world application for personalizing user-interface actions to individual users. Sycophant, our context

XCS Applied to Mapping FPGA Architectures

by Martin Danek, R. E. Smith - In Proceedings of the 2002 Genetic and Evolutionary Computation Conference – Gecco 2002 , 2002
"... This paper considers the application of XCS to the complex, real-world problem of mapping Boolean networks to technology-specific layout of field programmable gate arrays (FPGAs). The mapping is formulated as a temporal task, where the XCS’s actions are to create blocks (based on an abstract Boolean ..."
Abstract - Cited by 3 (0 self) - Add to MetaCart
This paper considers the application of XCS to the complex, real-world problem of mapping Boolean networks to technology-specific layout of field programmable gate arrays (FPGAs). The mapping is formulated as a temporal task, where the XCS’s actions are to create blocks (based on an abstract

Evolving Optimal Populations with XCS Classifier Systems

by Tim Kovacs , 1996
"... This work investigates some uses of self-monitoring in classifier systems (CS) using Wilson's recent XCS system as a framework. XCS is a significant advance in classifier systems technology which shifts the basis of fitness evaluation for the Genetic Algorithm (GA) from the strength of payoff p ..."
Abstract - Cited by 49 (11 self) - Add to MetaCart
can reliably evolve optimal populations (solutions), is proposed. An optimal population is one which accurately maps inputs to actions to reward predictions using the smallest possible set of classifiers. An optimal XCS population forms a complete mapping of the payoff environment in the reinforcement

Discrete Dynamical Genetic Programming in XCS

by Richard Preen, Larry Bull
"... A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results from an investigation into using a discrete dynamical system representation within the XCS Learning Classifier System. In p ..."
Abstract - Cited by 4 (2 self) - Add to MetaCart
. In particular, asynchronous random Boolean networks are used to represent the traditional condition-action production system rules. It is shown possible to use self-adaptive, open-ended evolution to design an ensemble of such discrete dynamical systems within XCS to solve a number of well-known test problems

Standard and averaging reinforcement learning in XCS

by Pier Luca Lanzi, Daniele Loiacono - GECCO 2006: Proceedings of the 8th annual conference on genetic and evolutionary computation , 2006
"... This paper investigates reinforcement learning (RL) in XCS. First, it formally shows that XCS implements a method of generalized RL based on linear approximators, in which the usual input mapping function translates the state-action space into a niche relative fitness space. Then, it shows that, alt ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
This paper investigates reinforcement learning (RL) in XCS. First, it formally shows that XCS implements a method of generalized RL based on linear approximators, in which the usual input mapping function translates the state-action space into a niche relative fitness space. Then, it shows that

Adaptive mobile robot navigation and mapping

by Hans Jacob S. Feder, John J. Leonard, Christopher M. Smith - International Journal of Robotics Research
"... The task of building a map of an unknown environment and concurrently using that map to navigate is a central problem in mobile robotics research. This paper addresses the problem of how to perform concurrent mapping and localization (CML) adaptively using sonar. Stochastic mapping is a feature-base ..."
Abstract - Cited by 126 (11 self) - Add to MetaCart
The task of building a map of an unknown environment and concurrently using that map to navigate is a central problem in mobile robotics research. This paper addresses the problem of how to perform concurrent mapping and localization (CML) adaptively using sonar. Stochastic mapping is a feature

Aliasing in XCS and the Consecutive State Problem: 1 - Effects

by Alwyn Barry , 1999
"... Whilst XCS (Wilson, 1998) has been shown to be more robust and reliable than previous LCS implementations (Kovacs, 1996, 1997), Lanzi (1997) identified a potential problem in the application of XCS to certain simple multi-step non Markovian environments. The 'Aliasing Problem' occurs ..."
Abstract - Cited by 2 (1 self) - Add to MetaCart
;Consecutive State Problem' and uses the subclass to identify the effects of consecutive state aliasing on the learning of the State Action Payoff mapping within XCS. It is shown that aliasing states can prevent the formation of classifiers covering preceding states due to the trade-off of accuracy

XCS Classifier System Reliably Evolves Accurate, Complete, and Minimal Representations for Boolean Functions

by Tim Kovacs , 1997
"... This paper extends the work presented in (Kovacs, 1996) on evolving optimal solutions to boolean reinforcement learning problems using Wilson's recent XCS classifier system. XCS forms complete mappings of the payoff environment in the reinforcement learning tradition thanks to its accuracy b ..."
Abstract - Cited by 51 (7 self) - Add to MetaCart
map all input/action pairs to payoff predictions using the smallest possible set of nonoverlapping classifiers. The ability of XCS to evolve optimal populations for boolean multiplexer problems was demonstrated in (Kovacs, 1996) using condensation, a technique in which evolutionary search

Information Based Adaptive Robotic Exploration

by Frederic Bourgault, Alexei A. Makarenko, Stefan B. Williams, Ben Grocholsky, Hugh F. Durrant-Whyte - in Proceedings IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS , 2002
"... Exploration involving mapping and concurrent localization in an unknown environment is a pervasive task in mobile robotics. In general, the accuracy of the mapping process depends directly on the accuracy of the localization process. This paper address the problem of maximizing the accuracy of the m ..."
Abstract - Cited by 94 (0 self) - Add to MetaCart
of the map building process during exploration by adaptively selecting control actions that maximize localisation accuracy. The map building and exploration task is modeled using an Occupancy Grid (OG) with concurrent localisation performed using a feature-based Simultaneous Localisation And Mapping (SLAM
Results 1 - 10 of 489