Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
On the editing distance between unordered labeled trees
Information Processing Letters
Seeing the light: artificial evolution, real vision
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
Automatic creation of an autonomous agent: genetic evolution of a neural-network driven robot
SAB94 Proceedings of the third international conference on Simulation of adaptive behavior : from animals to animats 3: from animals to animats 3
Automatic definition of modular neural networks
Adaptive Behavior
A graph distance metric based on the maximal common subgraph
Pattern Recognition Letters
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Evolving neural networks through augmenting topologies
Evolutionary Computation
Evolutionary Robotics: A Survey of Applications and Problems
Proceedings of the First European Workshop on Evolutionary Robotics
A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
Every Niching Method has its Niche: Fitness Sharing and Implicit Sharing Compared
PPSN IV Proceedings of the 4th International Conference on Parallel Problem Solving from Nature
A Racing Algorithm for Configuring Metaheuristics
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Reducing Local Optima in Single-Objective Problems by Multi-objectivization
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Genetic diversity as an objective in multi-objective evolutionary algorithms
Evolutionary Computation
Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines
Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines
A fast technique for comparing graph representations with applications to performance evaluation
International Journal on Document Analysis and Recognition
Diversity as a selection pressure in dynamic environments
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Behavior-based speciation for evolutionary robotics
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Theoretical analysis of diversity mechanisms for global exploration
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Incremental Evolution of Animats' Behaviors as a Multi-objective Optimization
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
Sustaining diversity using behavioral information distance
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
How novelty search escapes the deceptive trap of learning to learn
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Using behavioral exploration objectives to solve deceptive problems in neuro-evolution
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Single step evolution of robot controllers for sequential tasks
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
An improved small-sample statistical test for comparing the success rates of evolutionary algorithms
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Comparing parameter tuning methods for evolutionary algorithms
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Overcoming the bootstrap problem in evolutionary robotics using behavioral diversity
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Searching under multi-evolutionary pressures
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Evolving neural networks for the control of a lenticular blimp
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
Discovering several robot behaviors through speciation
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Guarding against premature convergence while accelerating evolutionary search
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Sustaining behavioral diversity in NEAT
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Confidence intervals of success rates in evolutionary computation
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Abandoning objectives: Evolution through the search for novelty alone
Evolutionary Computation
Incremental evolution of target-following neuro-controllers for flapping-wing animats
SAB'06 Proceedings of the 9th international conference on From Animals to Animats: simulation of Adaptive Behavior
Fitness sharing and niching methods revisited
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Neural Networks
Emergence of memory in neuroevolution: impact of selection pressures
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Evolving team behaviors with specialization
Genetic Programming and Evolvable Machines
Searching for novel classifiers
EuroGP'13 Proceedings of the 16th European conference on Genetic Programming
MONEE: using parental investment to combine open-ended and task-driven evolution
EvoApplications'13 Proceedings of the 16th European conference on Applications of Evolutionary Computation
Effective diversity maintenance in deceptive domains
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Right on the MONEE: combining task- and environment-driven evolution
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Generic behaviour similarity measures for evolutionary swarm robotics
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Searching for novel clustering programs
Proceedings of the 15th annual conference on Genetic and evolutionary computation
A behavior-based analysis of modal problems
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Toward nonlinear local reinforcement learning rules through neuroevolution
Neural Computation
Encouraging reactivity to create robust machines
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Fast damage recovery in robotics with the T-resilience algorithm
International Journal of Robotics Research
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Evolutionary robotics (ER) aims at automatically designing robots or controllers of robots without having to describe their inner workings. To reach this goal, ER researchers primarily employ phenotypes that can lead to an infinite number of robot behaviors and fitness functions that only reward the achievement of the task-and not how to achieve it. These choices make ER particularly prone to premature convergence. To tackle this problem, several papers recently proposed to explicitly encourage the diversity of the robot behaviors, rather than the diversity of the genotypes as in classic evolutionary optimization. Such an approach avoids the need to compute distances between structures and the pitfalls of the noninjectivity of the phenotype/behavior relation; however, it also introduces new questions: how to compare behavior? should this comparison be task specific? and what is the best way to encourage diversity in this context? In this paper, we review the main published approaches to behavioral diversity and benchmark them in a common framework. We compare each approach on three different tasks and two different genotypes. The results show that fostering behavioral diversity substantially improves the evolutionary process in the investigated experiments, regardless of genotype or task. Among the benchmarked approaches, multi-objective methods were the most efficient and the generic, Hamming-based, behavioral distance was at least as efficient as task specific behavioral metrics.