Active perception and reinforcement learning
Proceedings of the seventh international conference (1990) on Machine learning
Vision, instruction, and action
Vision, instruction, and action
Genetic programming (videotape): the movie
Genetic programming (videotape): the movie
Evolving visually guided robots
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Active Perception
The ALIVE system: full-body interaction with autonomous agents
CA '95 Proceedings of the Computer Animation
Reference frames for animate vision
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Generative learning of visual concepts using multiobjective genetic programming
Pattern Recognition Letters
Generality versus size in genetic programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Genetic programming as strategy for learning image descriptor operators
Intelligent Data Analysis
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Traditional machine vision assumes that the vision system recovers a complete, labeled description of the world [10]. Recently, several researchers have criticized this model and proposed an alternative model that considers perception as a distributed collection of task-specific, context-driven visual routines [1, 12]. Some of these researchers have argued that in natural living systems these visual routines are the product of natural selection [11]. So far, researchers have hand-coded task-specific visual routines for actual implementations (e.g., [3]). In this article we propose an alternative approach in which visual routines for simple tasks are created using an artificial evolution approach. We present results from a series of runs on actual camera images, in which simple routines were evolved using genetic programming techniques [7]. The results obtained are promising: The evolved routines are able to process correctly up to 93% of the test images, which is better than any algorithm we were able to write by hand.