What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Programming language
- Operating system
Programming language, Artificial intelligence, Programming paradigm, Functional logic programming and Semantics are his primary areas of study.
His studies link 3APL with Programming language.
John-Jules Ch. Meyer works in the field of Artificial intelligence, namely Intelligent agent.
He works mostly in the field of Functional logic programming, limiting it down to topics relating to Programming language theory and, in certain cases, First-generation programming language and Semantics of logic, as a part of the same area of interest.
His Semantics research incorporates elements of Semantics, Philosophy of language, Cognitive model, Recursion and Formalism.
His studies in Dynamic logic integrate themes in fields like Epistemic modal logic, Multimodal logic, Deontic logic and Philosophy of logic.
His most cited work include:
- Epistemic logic for AI and computer science (438 citations)
- Agent Programming in 3APL (361 citations)
- A different approach to deontic logic: deontic logic viewed as a variant of dynamic logic. (338 citations)
What are the main themes of his work throughout his whole career to date?
John-Jules Ch. Meyer mainly investigates Artificial intelligence, Programming language, Multi-agent system, Intelligent agent and Knowledge management.
As part of the same scientific family, John-Jules Ch. Meyer usually focuses on Artificial intelligence, concentrating on Dynamic logic and intersecting with Multimodal logic and Deontic logic.
His study in Operational semantics, Functional logic programming, Programming paradigm, Semantics and Fifth-generation programming language are all subfields of Programming language.
His research in Functional logic programming intersects with topics in Programming language theory and Logic programming.
He has researched Programming language theory in several fields, including First-generation programming language and Programming domain.
As a part of the same scientific family, John-Jules Ch. Meyer mostly works in the field of Semantics, focusing on Semantics and, on occasion, 3APL.
He most often published in these fields:
- Artificial intelligence (29.26%)
- Programming language (16.59%)
- Multi-agent system (12.44%)
What were the highlights of his more recent work (between 2013-2021)?
- Artificial intelligence (29.26%)
- Multi-agent system (12.44%)
- Opportunism (2.07%)
In recent papers he was focusing on the following fields of study:
His main research concerns Artificial intelligence, Multi-agent system, Opportunism, Manufacturing engineering and Normative.
His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning and Task.
His work deals with themes such as Intelligent agent, Common knowledge, Autonomous agent and Logical framework, which intersect with Multi-agent system.
John-Jules Ch. Meyer interconnects Linear temporal logic, Theoretical computer science, Sketch, Cognitive science and Complex system in the investigation of issues within Normative.
His studies deal with areas such as Model checking, Syntax and Semantics as well as Linear temporal logic.
His Syntax study deals with the bigger picture of Programming language.
Between 2013 and 2021, his most popular works were:
- Adaptive emotional expression in robot-child interaction (75 citations)
- A two-phase method for extracting explanatory arguments from Bayesian networks (35 citations)
- A structure-guided approach to capturing bayesian reasoning about legal evidence in argumentation (17 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Algebra
John-Jules Ch. Meyer mainly focuses on Artificial intelligence, Bayesian network, Probabilistic logic, Graph and Argumentation theory.
His Artificial intelligence research is multidisciplinary, relying on both Machine learning and Management science.
His Dynamic Bayesian network study in the realm of Bayesian network interacts with subjects such as Variable-order Bayesian network.
His work in Graph addresses subjects such as Interpretation, which are connected to disciplines such as Function and Context.
Within one scientific family, John-Jules Ch. Meyer focuses on topics pertaining to Multi-agent system under Context, and may sometimes address concerns connected to Normative.
John-Jules Ch. Meyer has included themes like Argumentative and Data science in his Argumentation theory study.
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