H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Engineering and Technology H-index 31 Citations 5,818 138 World Ranking 5931 National Ranking 420

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Artificial neural network

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.

His most cited work include:

  • Noise and the Reality Gap: The Use of Simulation in Evolutionary Robotics (449 citations)
  • Explorations in evolutionary robotics (343 citations)
  • Evolutionary Robotics: the Sussex Approach (232 citations)

What are the main themes of his work throughout his whole career to date?

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.

He most often published in these fields:

  • Artificial intelligence (38.00%)
  • Robot (20.40%)
  • Artificial neural network (16.00%)

What were the highlights of his more recent work (between 2011-2021)?

  • Artificial intelligence (38.00%)
  • Evolutionary robotics (15.60%)
  • Cognitive science (6.80%)

In recent papers he was focusing on the following fields of study:

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.

Between 2011 and 2021, his most popular works were:

  • Selectionist and evolutionary approaches to brain function: a critical appraisal. (58 citations)
  • The Horizons of Evolutionary Robotics (44 citations)
  • Evolution of Associative Learning in Chemical Networks (31 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Artificial neural network

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.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Noise and the Reality Gap: The Use of Simulation in Evolutionary Robotics

Nick Jacobi;Phil Husbands;Inman Harvey.
european conference on artificial life (1995)

647 Citations

Explorations in evolutionary robotics

Dave Cliff;Phil Husbands;Inman Harvey.
Adaptive Behavior (1993)

588 Citations

Evolutionary Robotics: the Sussex Approach

Inman Harvey;Phil Husbands;Dave Cliff;Adrian Thompson.
Robotics and Autonomous Systems (1997)

388 Citations

Seeing the light: artificial evolution, real vision

Inman Harvey;Phil Husbands;Dave Cliff.
simulation of adaptive behavior (1994)

355 Citations

Simulated Co-Evolution as the Mechanism for Emergent Planning and Scheduling.

Phil Husbands;Frank Mill.
ICGA (1991)

265 Citations

Evolution of central pattern generators for bipedal walking in a real-time physics environment

T. Reil;P. Husbands.
IEEE Transactions on Evolutionary Computation (2002)

240 Citations

Fitness landscapes and evolvability

Tom Smith;Phil Husbands;Paul Layzell;Michael O'Shea.
Evolutionary Computation (2002)

223 Citations

Better Living Through Chemistry: Evolving GasNets for Robot Control

Phil Husbands;Tom Smith;Nick Jakobi;Michael O'Shea.
Connection Science (1998)

187 Citations

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)

175 Citations

Fourth European Conference on Artificial Life

Phil Husbands;Inman Harvey.
(1997)

173 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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