Phil Husbands mainly investigates Artificial intelligence, Evolutionary algorithm, Evolutionary robotics, Robot and Genetic algorithm. Phil Husbands regularly links together related areas like Mechanism in his Artificial intelligence studies. The study incorporates disciplines such as Fitness landscape, Neutral theory of molecular evolution, Fitness function, Computer vision and Evolvability in addition to Evolutionary algorithm.
His Evolutionary robotics study incorporates themes from Robotics, Robot control, Neutral network and Simulation. His work on Mobile robot as part of his general Robot study is frequently connected to Asynchronous communication, thereby bridging the divide between different branches of science. His study in the field of Genetic representation also crosses realms of Multi criteria and Sorting network.
Artificial intelligence, Robot, Artificial neural network, Evolutionary robotics and Evolutionary algorithm are his primary areas of study. His Artificial intelligence research includes themes of Machine learning, Evolvability and Cognition. His research in Robot intersects with topics in Control engineering, Control system and Human–computer interaction.
His primary area of study in Artificial neural network is in the field of Recurrent neural network. His study connects Genetic algorithm and Evolutionary algorithm. His Genetic algorithm research is included under the broader classification of Mathematical optimization.
His primary areas of study are Artificial intelligence, Evolutionary robotics, Cognitive science, Robot and Chaotic. His Artificial intelligence research incorporates themes from Machine learning and Cognition. His Evolutionary robotics research incorporates elements of Context and Neuroscience.
In Cognitive science, Phil Husbands works on issues like Developmental robotics, which are connected to Bio-inspired computing and Field. His work in Robot addresses issues such as Human–computer interaction, which are connected to fields such as Minimal model. His Control engineering study which covers Evolutionary algorithm that intersects with Machine tool.
Phil Husbands mostly deals with Artificial intelligence, Process, Evolutionary robotics, Machine learning and Evolvability. His research in Artificial intelligence is mostly focused on Variation. His Evolutionary robotics study integrates concerns from other disciplines, such as Chaotic and Embodied cognition.
His Feature selection, Spiking neural network and Unsupervised learning study in the realm of Machine learning interacts with subjects such as Biochemical Phenomena. His work carried out in the field of Evolvability brings together such families of science as Elementary cognitive task, Kuramoto model and Morphology. His research in Cognitive science tackles topics such as Robotics which are related to areas like Evolutionary computation.
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Noise and the Reality Gap: The Use of Simulation in Evolutionary Robotics
Nick Jacobi;Phil Husbands;Inman Harvey.
european conference on artificial life (1995)
Explorations in evolutionary robotics
Dave Cliff;Phil Husbands;Inman Harvey.
Adaptive Behavior (1993)
Evolutionary Robotics: the Sussex Approach
Inman Harvey;Phil Husbands;Dave Cliff;Adrian Thompson.
Robotics and Autonomous Systems (1997)
Seeing the light: artificial evolution, real vision
Inman Harvey;Phil Husbands;Dave Cliff.
simulation of adaptive behavior (1994)
Simulated Co-Evolution as the Mechanism for Emergent Planning and Scheduling.
Phil Husbands;Frank Mill.
Evolution of central pattern generators for bipedal walking in a real-time physics environment
T. Reil;P. Husbands.
IEEE Transactions on Evolutionary Computation (2002)
Fitness landscapes and evolvability
Tom Smith;Phil Husbands;Paul Layzell;Michael O'Shea.
Evolutionary Computation (2002)
Better Living Through Chemistry: Evolving GasNets for Robot Control
Phil Husbands;Tom Smith;Nick Jakobi;Michael O'Shea.
Connection Science (1998)
Evolving controllers for a homogeneous system of physical robots: structured cooperation with minimal sensors.
Matt Quinn;Lincoln Smith;Giles Mayley;Phil Husbands.
Philosophical Transactions of the Royal Society A (2003)
Four-Dimensional Neuronal Signaling by Nitric Oxide: A Computational Analysis
Andrew Philippides;Phil Husbands;Michael O'Shea.
The Journal of Neuroscience (2000)
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