Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Adaptive Behavior
Cambrian intelligence: the early history of the new AI
Cambrian intelligence: the early history of the new AI
The Simple Genetic Algorithm: Foundations and Theory
The Simple Genetic Algorithm: Foundations and Theory
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Solving Partially Observable Problems by Evolution and Learning of Finite State Machines
ICES '01 Proceedings of the 4th International Conference on Evolvable Systems: From Biology to Hardware
Motor primitive and sequence self-organization in a hierarchical recurrent neural network
Neural Networks - 2004 Special issue: New developments in self-organizing systems
State Space Segmentation for Acquisition of Agent Behavior
IAT '06 Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology
Fuzzy Q-Learning with the modified fuzzy ART neural network
Web Intelligence and Agent Systems
Improving the Behavior of Creatures by Time-Shuffling
ACRI '08 Proceedings of the 8th international conference on Cellular Automata for Reseach and Industry
State space segmentation for acquisition of agent behavior
Web Intelligence and Agent Systems
Itinerary determination of imprecise mobile agents with firm deadline
Web Intelligence and Agent Systems
On the Effectiveness of Evolution Compared to Time-Consuming Full Search of Optimal 6-State Automata
EuroGP '09 Proceedings of the 12th European Conference on Genetic Programming
Solving All-to-All Communication with CA Agents More Effectively with Flags
PaCT '09 Proceedings of the 10th International Conference on Parallel Computing Technologies
Solving the exploration's problem with several creatures more efficiently
EUROCAST'07 Proceedings of the 11th international conference on Computer aided systems theory
All-to-all communication with CA agents by active coloring and acknowledging
ACRI'10 Proceedings of the 9th international conference on Cellular automata for research and industry
Optimal 6-state algorithms for the behavior of several moving creatures
ACRI'06 Proceedings of the 7th international conference on Cellular Automata for Research and Industry
Are several creatures more efficient than a single one?
ACRI'06 Proceedings of the 7th international conference on Cellular Automata for Research and Industry
Optimal behavior of a moving creature in the cellular automata model
PaCT'05 Proceedings of the 8th international conference on Parallel Computing Technologies
parallel hardware architecture to simulate movable creatures in the CA model
PaCT'07 Proceedings of the 9th international conference on Parallel Computing Technologies
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We present SOS++, a bioinspired method combining evolution and learning, allowing the automatic design of the controller of autonomous agents, described as a finite-state machine. The application of this method to well-known problems, for example the follow-up of a trail or the resolution of a maze, led to the emergence of some behaviors we could qualify as intelligent. Moreover, it is possible to use the method in a hierarchical way in order to obtain complex behaviors starting from a set of basic actions. We have used an algorithm which is a variation of reinforcement learning with a reward adapted to the degree of uncertainty of the performed prediction.