What is he best known for?
The fields of study he is best known for:
- Computer network
- Artificial intelligence
- Statistics
Tamer Basar focuses on Mathematical optimization, Game theory, Nash equilibrium, Control theory and Distributed computing.
His work on Stochastic control as part of general Mathematical optimization research is frequently linked to Context, bridging the gap between disciplines.
In general Game theory, his work in Game theoretic is often linked to Smart grid linking many areas of study.
Nash equilibrium is a subfield of Mathematical economics that Tamer Basar investigates.
Tamer Basar has included themes like State and Estimator in his Control theory study.
His work carried out in the field of Distributed computing brings together such families of science as Network congestion, Stochastic game, Intrusion detection system, The Internet and Computer network.
His most cited work include:
- Dynamic Noncooperative Game Theory (3322 citations)
- Coalitional game theory for communication networks (768 citations)
- Quantized consensus (622 citations)
What are the main themes of his work throughout his whole career to date?
Mathematical optimization, Control theory, Nash equilibrium, Game theory and Optimal control are his primary areas of study.
His Mathematical optimization study integrates concerns from other disciplines, such as Stackelberg competition, Stochastic process, Decision problem and Function.
His Bounded function research extends to Control theory, which is thematically connected.
Nash equilibrium is a subfield of Mathematical economics that he explores.
Tamer Basar is interested in Repeated game, which is a branch of Mathematical economics.
As part of one scientific family, Tamer Basar deals mainly with the area of Game theory, narrowing it down to issues related to the Computer network, and often Wireless.
He most often published in these fields:
- Mathematical optimization (33.99%)
- Control theory (17.55%)
- Nash equilibrium (16.06%)
What were the highlights of his more recent work (between 2015-2021)?
- Mathematical optimization (33.99%)
- Nash equilibrium (16.06%)
- Reinforcement learning (3.83%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Mathematical optimization, Nash equilibrium, Reinforcement learning, Discrete mathematics and Stackelberg competition.
His Mathematical optimization research includes themes of Function, Control and Control theory.
His Nash equilibrium study is focused on Mathematical economics in general.
His Reinforcement learning study incorporates themes from Convergence and Algorithm.
His studies in Convergence integrate themes in fields like Telecommunications network and Sequence.
Many of his studies on Discrete mathematics apply to Combinatorics as well.
Between 2015 and 2021, his most popular works were:
- Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms. (126 citations)
- Demand Response Management in the Smart Grid in a Large Population Regime (115 citations)
- Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents (85 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Artificial intelligence
- Statistics
Tamer Basar mostly deals with Mathematical optimization, Reinforcement learning, Discrete mathematics, Nash equilibrium and Convergence.
His Mathematical optimization study combines topics from a wide range of disciplines, such as Stackelberg competition, Stochastic process and Discrete time and continuous time.
His work deals with themes such as Algorithm, Control theory and Nonlinear system, which intersect with Reinforcement learning.
His Nonlinear system research incorporates themes from Telecommunications network and Theoretical computer science.
His Discrete mathematics research is multidisciplinary, incorporating elements of Distributed algorithm and Graph, Combinatorics.
Nash equilibrium is a primary field of his research addressed under Mathematical economics.
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