TY - GEN
T1 - Sampling bias in estimation of distribution algorithms for genetic programming using prototype trees
AU - Kim, Kangil
AU - McKay, Bob
AU - Punithan, Dharani
PY - 2010
Y1 - 2010
N2 - Probabilistic models are widely used in evolutionary and related algorithms. In Genetic Programming (GP), the Probabilistic Prototype Tree (PPT) is often used as a model representation. Drift due to sampling bias is a widely recognised problem, and may be serious, particularly in dependent probability models. While this has been closely studied in independent probability models, and more recently in probabilistic dependency models, it has received little attention in systems with strict dependence between probabilistic variables such as arise in PPT representation. Here, we investigate this issue, and present results suggesting that the drift effect in such models may be particularly severe - so severe as to cast doubt on their scalability. We present a preliminary analysis through a factor representation of the joint probability distribution. We suggest future directions for research aiming to overcome this problem.
AB - Probabilistic models are widely used in evolutionary and related algorithms. In Genetic Programming (GP), the Probabilistic Prototype Tree (PPT) is often used as a model representation. Drift due to sampling bias is a widely recognised problem, and may be serious, particularly in dependent probability models. While this has been closely studied in independent probability models, and more recently in probabilistic dependency models, it has received little attention in systems with strict dependence between probabilistic variables such as arise in PPT representation. Here, we investigate this issue, and present results suggesting that the drift effect in such models may be particularly severe - so severe as to cast doubt on their scalability. We present a preliminary analysis through a factor representation of the joint probability distribution. We suggest future directions for research aiming to overcome this problem.
UR - http://www.scopus.com/inward/record.url?scp=78049257405&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-15246-7_12
DO - 10.1007/978-3-642-15246-7_12
M3 - Conference contribution
SN - 3642152457
SN - 9783642152450
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 100
EP - 111
BT - PRICAI 2010
T2 - 11th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2010
Y2 - 30 August 2010 through 2 September 2010
ER -