What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Programming language
- Machine learning
Victor Lesser mainly investigates Artificial intelligence, Distributed computing, Task, Multi-agent system and Process.
Victor Lesser regularly ties together related areas like Domain in his Artificial intelligence studies.
His Distributed computing study combines topics in areas such as Node, Control, Cooperative distributed problem solving and Asynchronous communication.
His Task research includes elements of Rational agent and Machine learning.
The Multi-agent system study combines topics in areas such as Mathematical optimization, Key, Game theory and Stochastic game.
His Process research integrates issues from Abstraction, Context, Management information systems, Knowledge management and Operations research.
His most cited work include:
- The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty (1208 citations)
- A survey of multi-agent organizational paradigms (548 citations)
- Coalitions among computationally bounded agents (406 citations)
What are the main themes of his work throughout his whole career to date?
Artificial intelligence, Distributed computing, Multi-agent system, Process and Knowledge management are his primary areas of study.
The various areas that Victor Lesser examines in his Artificial intelligence study include Machine learning, Task and State.
Victor Lesser has included themes like Resource allocation, Cooperative distributed problem solving, Wireless sensor network, Testbed and Scheduling in his Distributed computing study.
Victor Lesser focuses mostly in the field of Multi-agent system, narrowing it down to matters related to Mathematical optimization and, in some cases, Algorithm.
His research integrates issues of Domain, Context, Resource, Adaptation and Operations research in his study of Process.
His studies in Knowledge management integrate themes in fields like Human–computer interaction and Process management.
He most often published in these fields:
- Artificial intelligence (29.54%)
- Distributed computing (27.35%)
- Multi-agent system (18.38%)
What were the highlights of his more recent work (between 2008-2020)?
- Artificial intelligence (29.54%)
- Multi-agent system (18.38%)
- Mathematical optimization (12.91%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Artificial intelligence, Multi-agent system, Mathematical optimization, Reinforcement learning and Distributed computing.
His research in Artificial intelligence focuses on subjects like Key, which are connected to Set.
His work deals with themes such as Context, Autonomous agent, Theoretical computer science and Management science, which intersect with Multi-agent system.
His Mathematical optimization research is multidisciplinary, relying on both Algorithm and Computation.
His Distributed computing study also includes fields such as
- Scalability and related Property,
- Resource allocation together with Operations research and Resource.
His work in Adaptation covers topics such as Control which are related to areas like Knowledge management.
Between 2008 and 2020, his most popular works were:
- Automated negotiation with decommitment for dynamic resource allocation in cloud computing (168 citations)
- A Survey of Multi-Agent Trust Management Systems (152 citations)
- Coordinating multi-agent reinforcement learning with limited communication (80 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Programming language
- Machine learning
Artificial intelligence, Reinforcement learning, Resource allocation, Distributed computing and Multi-agent system are his primary areas of study.
His Artificial intelligence study integrates concerns from other disciplines, such as Machine learning and Scalability.
His study in Reinforcement learning is interdisciplinary in nature, drawing from both Adaptation and Distributed constraint optimization.
Victor Lesser interconnects Resource and Mathematical optimization, Nash equilibrium in the investigation of issues within Resource allocation.
He has researched Distributed computing in several fields, including Genetic algorithm and Set.
His Multi-agent system research includes elements of Testbed, Context and Wireless sensor network.
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