What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Programming language
His primary scientific interests are in Artificial intelligence, Evolutionary algorithm, Robot, Mathematical optimization and Artificial life.
The Artificial intelligence study combines topics in areas such as Machine learning and Coevolution.
The study incorporates disciplines such as Evolutionary computation and Genetic programming in addition to Evolutionary algorithm.
His work on Evolutionary robotics and Robotics is typically connected to Division of labour as part of general Robot study, connecting several disciplines of science.
His biological study spans a wide range of topics, including Simple function, Initial value problem and Task.
His Artificial life study combines topics in areas such as Animation, Intelligent agent, Natural, Computer graphics and Variety.
His most cited work include:
- An evolutionary algorithm that constructs recurrent neural networks (865 citations)
- Recursive distributed representations (729 citations)
- Automatic design and manufacture of robotic lifeforms (725 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Artificial intelligence, Robot, Theoretical computer science, Artificial neural network and Evolutionary algorithm.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Genetic algorithm and Machine learning.
His study of Evolutionary robotics is a part of Robot.
His research combines Evolutionary computation and Evolutionary algorithm.
He most often published in these fields:
- Artificial intelligence (43.52%)
- Robot (10.66%)
- Theoretical computer science (8.93%)
What were the highlights of his more recent work (between 2005-2021)?
- Artificial intelligence (43.52%)
- Robot (10.66%)
- Theoretical computer science (8.93%)
In recent papers he was focusing on the following fields of study:
Jordan Pollack mainly investigates Artificial intelligence, Robot, Theoretical computer science, Gene regulatory network and Artificial neural network.
His research on Artificial intelligence often connects related areas such as Modular design.
His study on Self-reconfiguring modular robot is often connected to Specialization as part of broader study in Robot.
His study looks at the intersection of Theoretical computer science and topics like Coevolution with Competition and Metric.
His research investigates the connection between Artificial neural network and topics such as Neural population that intersect with problems in Parallels and Evolutionary game theory.
His study explores the link between Evolutionary computation and topics such as Mobile robot that cross with problems in Machine learning and Reinforcement learning.
Between 2005 and 2021, his most popular works were:
- Method and apparatus for distributing information to users (173 citations)
- Imaging analysis of clock neurons reveals light buffers the wake-promoting effect of dopamine (92 citations)
- Gene Regulatory Network Evolution Through Augmenting Topologies (26 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Programming language
His scientific interests lie mostly in Artificial intelligence, Gene regulatory network, Human–computer interaction, Evolutionary computation and Mathematical economics.
His studies deal with areas such as Finite-state machine and Metric as well as Artificial intelligence.
His research in Human–computer interaction intersects with topics in Engineering drawing, Multimedia, Rapid prototyping, Robot and Object.
The concepts of his Robot study are interwoven with issues in Organism, Living systems, Multicellular organism and Plan.
The various areas that Jordan Pollack examines in his Evolutionary computation study include Context and Mobile robot.
His Mathematical economics research incorporates elements of Evolutionary dynamics, Attractor and Instability.
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