Fractals everywhere
Intelligence without representation
Artificial Intelligence
The Induction of Dynamical Recognizers
Machine Learning - Connectionist approaches to language learning
Temporal difference learning of backgammon strategy
ML92 Proceedings of the ninth international workshop on Machine learning
Extracting and representing qualitative behaviors of complex systems in phase space
Artificial Intelligence
The sciences of the artificial (3rd ed.)
The sciences of the artificial (3rd ed.)
Co-Evolution in the Successful Learning of Backgammon Strategy
Machine Learning
Competitive Environments Evolve Better Solutions for Complex Tasks
Proceedings of the 5th International Conference on Genetic Algorithms
Dynamic Programming
On the Robustness Achievable with Stochastic Development Processes
EH '05 Proceedings of the 2005 NASA/DoD Conference on Evolvable Hardware
Evolving Assembly Plans for Fully Automated Design and Assembly
EH '05 Proceedings of the 2005 NASA/DoD Conference on Evolvable Hardware
Evolutionary Body Building: Adaptive Physical Designs for Robots
Artificial Life
Ideal Evaluation from Coevolution
Evolutionary Computation
Motivating Appropriate Challenges in a Reciprocal Tutoring System
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
Focusing versus intransitivity: geometrical aspects of co-evolution
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Automatic discovery of self-replicating structures in cellularautomata
IEEE Transactions on Evolutionary Computation
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AI was founded on a mistaken goal. Trying to create human-level intelligence by simulating cognitive architecture, often discovered via introspective protocols, is practically impossible owing to the limits of software engineering. However, many processes in nature are much more powerful than human symbolic thought. These exquisitely iterative systems, such as evolution and embryogenesis, don't require logic, grammar, or other accoutrements of anthropomorphic cognitive architecture. Successfully studying intelligence as it arises outside the human mind, rather than failing to deliver on the old promises of human-level performance, will put the field on a sturdier scientific and fiscal foundation.This article is part of a special issue on the Future of AI.