What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Algorithm
- Machine learning
His primary areas of investigation include Evolutionary algorithm, Artificial intelligence, Complex network, Mathematical optimization and Genetic programming.
His Evolutionary algorithm research incorporates themes from Theoretical computer science, Lattice, Evolutionary computation and Algorithm, Cellular automaton.
As part of his studies on Theoretical computer science, he often connects relevant subjects like Random number generation.
Many of his studies involve connections with topics such as Machine learning and Artificial intelligence.
He has researched Complex network in several fields, including Fitness landscape, Evolutionary stability, Social dilemma and Transient.
His work on Genetic representation as part of general Genetic programming research is often related to Test case, thus linking different fields of science.
His most cited work include:
- Parallelism and evolutionary algorithms (708 citations)
- A phylogenetic, ontogenetic, and epigenetic view of bio-inspired hardware systems (193 citations)
- On the generation of high-quality random numbers by two-dimensional cellular automata (128 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Theoretical computer science, Genetic programming, Artificial intelligence, Cellular automaton and Mathematical optimization.
His Theoretical computer science research includes themes of Evolutionary algorithm, Random graph and Complex network.
He has included themes like Evolutionary computation and Selection in his Evolutionary algorithm study.
His research on Genetic programming also deals with topics like
- Genetic algorithm which is related to area like Parallel algorithm,
- Fitness function which is related to area like Distance correlation.
Artificial intelligence is closely attributed to Machine learning in his work.
The study incorporates disciplines such as Fitness landscape and Set in addition to Mathematical optimization.
He most often published in these fields:
- Theoretical computer science (28.24%)
- Genetic programming (23.92%)
- Artificial intelligence (21.59%)
What were the highlights of his more recent work (between 2012-2021)?
- Theoretical computer science (28.24%)
- Local optimum (9.30%)
- Complex network (9.30%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Theoretical computer science, Local optimum, Complex network, Dilemma and Metaheuristic.
His work carried out in the field of Theoretical computer science brings together such families of science as Evolutionary algorithm, Network model, Artificial intelligence and Random graph.
The Artificial intelligence study combines topics in areas such as Path and Machine learning.
His Local optimum research includes elements of Fitness landscape, Quadratic assignment problem, Local optima networks and Local search.
Marco Tomassini interconnects Mathematical economics and Microeconomics in the investigation of issues within Dilemma.
His Metaheuristic study integrates concerns from other disciplines, such as Computational complexity theory and Nest.
Between 2012 and 2021, his most popular works were:
- Smart rewiring for network robustness (56 citations)
- Local Optima Networks: A New Model of Combinatorial Fitness Landscapes (39 citations)
- Random diffusion and cooperation in continuous two-dimensional space. (33 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Algorithm
- Machine learning
Dilemma, Mathematical optimization, Game theory, Local optimum and Theoretical computer science are his primary areas of study.
His research integrates issues of Mathematical economics, Microeconomics and Simulation in his study of Dilemma.
His biological study spans a wide range of topics, including Space, Landscape model and Flow shop scheduling.
His studies deal with areas such as Fitness landscape, Local optima networks, Operator and Problem difficulty as well as Local optimum.
His Fitness landscape research is multidisciplinary, incorporating perspectives in Quadratic assignment problem and Network model, Local search, Artificial intelligence.
His Theoretical computer science study incorporates themes from Coordination game and Random graph.
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