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EPS
1995
Springer
15 years 7 months ago
An Evolutionary Programming Approach to Self-Adaptation on Finite State Machines
Evolutionary programming was first offered as an alternative method for generating artificial intelligence. Experiments were offered in which finite state machines were used to...
Lawrence J. Fogel, Peter J. Angeline, David B. Fog...
126
Voted
GECCO
2000
Springer
178views Optimization» more  GECCO 2000»
15 years 7 months ago
Fitness Sharing in Genetic Programming
This paper investigates fitness sharing in genetic programming. Implicit fitness sharing is applied to populations of programs. Three treatments are compared: raw fitness, pure fi...
Robert I. McKay
SE
2008
15 years 5 months ago
Eliminating Trust From Application Programs By Way Of Software Architecture
: In many of today's application programs, security functionality is inseparably intertwined with the actual mission-purpose logic. As a result, the trusted code base is unnec...
Michael Franz
116
Voted
ICML
2008
IEEE
16 years 4 months ago
Apprenticeship learning using linear programming
In apprenticeship learning, the goal is to learn a policy in a Markov decision process that is at least as good as a policy demonstrated by an expert. The difficulty arises in tha...
Umar Syed, Michael H. Bowling, Robert E. Schapire
140
Voted
COCOA
2007
Springer
15 years 10 months ago
A New Dynamic Programming Algorithm for Multiple Sequence Alignment
Abstract. Multiple sequence alignment (MSA) is one of the most basic and central tasks for many studies in modern biology. In this paper, we present a new progressive alignment alg...
Jean-Michel Richer, Vincent Derrien, Jin-Kao Hao