What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Programming language
- Statistics
His primary areas of study are Knowledge management, Multi-agent system, Autonomous agent, Artificial intelligence and Management science.
His Knowledge management research includes themes of Structure, Regret, E-commerce and Formal specification.
His Multi-agent system research incorporates elements of Decision model, Software, Software agent and Internet privacy.
His Autonomous agent research incorporates themes from Business process management, Fuzzy set, Computational model and Operations research.
His Artificial intelligence research includes elements of Cognitive psychology, Formalism and Logical framework.
His research on Management science also deals with topics like
- Domain which is related to area like Argumentation theory,
- Multi issue, Negotiation system and Business economics most often made with reference to Buyer agent.
His most cited work include:
- Automated Negotiation: Prospects, Methods and Challenges (1249 citations)
- Negotiation Decision Functions for Autonomous Agents (1046 citations)
- Review on Computational Trust and Reputation Models (797 citations)
What are the main themes of his work throughout his whole career to date?
Carles Sierra focuses on Multi-agent system, Knowledge management, Artificial intelligence, Autonomous agent and Human–computer interaction.
The various areas that Carles Sierra examines in his Multi-agent system study include Management science, Computer security, Software agent, Software and Software engineering.
Carles Sierra has included themes like Agent architecture, Argumentation theory and Set in his Knowledge management study.
He regularly ties together related areas like Architecture in his Artificial intelligence studies.
His Robot study focuses on Mobile robot in particular.
He most often published in these fields:
- Multi-agent system (21.89%)
- Knowledge management (20.90%)
- Artificial intelligence (21.89%)
What were the highlights of his more recent work (between 2014-2020)?
- Knowledge management (20.90%)
- Multi-agent system (21.89%)
- World Wide Web (7.71%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Knowledge management, Multi-agent system, World Wide Web, Team composition and Management science.
His work focuses on many connections between Knowledge management and other disciplines, such as Service, that overlap with his field of interest in Knowledge transfer.
His study in Multi-agent system is interdisciplinary in nature, drawing from both Iterated function, Autonomous agent, Nash equilibrium and Dilemma.
His work deals with themes such as Distributed computing and Engineering management, which intersect with Autonomous agent.
His studies deal with areas such as DSPACE, Multimedia and Measure as well as World Wide Web.
The Management science study combines topics in areas such as Game theory and Ideal.
Between 2014 and 2020, his most popular works were:
- $$\hbox {NB}^{3}$$NB3: a multilateral negotiation algorithm for large, non-linear agreement spaces with limited time (24 citations)
- Probabilistic Planning in AgentSpeak using the POMDP framework. (11 citations)
- Probabilistic Planning in AgentSpeak using the POMDP framework. (11 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Statistics
Carles Sierra mainly focuses on Knowledge management, Team composition, Management science, Personality and Task.
His Knowledge management study combines topics in areas such as Affective computing, Multi-agent system and Decision support system.
His biological study spans a wide range of topics, including Crowdsourcing and Strengths and weaknesses.
His biological study spans a wide range of topics, including Human–computer interaction, Game theory, Ideal and Simple.
His Personality research incorporates elements of Mood, Cognitive psychology, Partition and Competence.
His study looks at the intersection of Competence and topics like Diversity with Set.
This overview was generated by a machine learning system which analysed the scientist’s
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