Tamás Bécsi

About Tamás Bécsi

Tamás Bécsi, With an exceptional h-index of 13 and a recent h-index of 11 (since 2020), a distinguished researcher at Budapesti Muszaki és Gazdaságtudományi Egyetem, specializes in the field of motion planning, reinforcement learning, autonomous vehicles, vehicle dynamics, machine learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Strategic Data Navigation: Information Value-based Sample Selection

Differentiable Particle Filtering using Optimal Placement Resampling

On the relationship between the activity at point of interests and road traffic

Multi-agent reinforcement learning for traffic signal control: A cooperative approach

Object-Level Data-Driven Sensor Simulation for Automotive Environment Perception

Comparison of Single-and Multi-Agent Reinforcement Learning for Highway Driving

A Runtime-Efficient Multi-Object Tracking Approach for Automotive Perception Systems

Multi-Agent Reinforcement Learning for Highway Platooning

Tamás Bécsi Information

University

Position

___

Citations(all)

771

Citations(since 2020)

619

Cited By

333

hIndex(all)

13

hIndex(since 2020)

11

i10Index(all)

23

i10Index(since 2020)

21

Email

University Profile Page

Budapesti Muszaki és Gazdaságtudományi Egyetem

Google Scholar

View Google Scholar Profile

Tamás Bécsi Skills & Research Interests

motion planning

reinforcement learning

autonomous vehicles

vehicle dynamics

machine learning

Top articles of Tamás Bécsi

Title

Journal

Author(s)

Publication Date

Strategic Data Navigation: Information Value-based Sample Selection

Csanád Levente Balogh

Bálint Pelenczei

Bálint Kővári

Tamás Bécsi

2024/3/26

Differentiable Particle Filtering using Optimal Placement Resampling

arXiv preprint arXiv:2402.16639

Domonkos Csuzdi

Olivér Törő

Tamás Bécsi

2024/2/26

On the relationship between the activity at point of interests and road traffic

Communications in Transportation Research

Máté Kolat

Tamás Tettamanti

Tamás Bécsi

Domokos Esztergár-Kiss

2023/12/1

Multi-agent reinforcement learning for traffic signal control: A cooperative approach

arXiv preprint arXiv:2204.12190

Qize Jiang

Minhao Qin

Shengmin Shi

Weiwei Sun

Baihua Zheng

2022/4/26

Object-Level Data-Driven Sensor Simulation for Automotive Environment Perception

IEEE Transactions on Intelligent Vehicles

László Lindenmaier

Szilárd Aradi

Tamás Bécsi

Olivér Törő

Péter Gáspár

2023/6/19

Comparison of Single-and Multi-Agent Reinforcement Learning for Highway Driving

IEEE CogMob 2023 (2nd IEEE International Conference on Cognitive Mobility)

Dániel Tamás Gujgiczer

Ádám Szabó

Tamás Bécsi

2023

A Runtime-Efficient Multi-Object Tracking Approach for Automotive Perception Systems

László Lindenmaier

Balázs Czibere

Szilárd Aradi

Tamás Bécsi

2023/5/23

Multi-Agent Reinforcement Learning for Highway Platooning

Electronics

Máté Kolat

Tamás Bécsi

2023/12/11

Analytic solution of the exact Daum–Huang flow equation for particle filters

Information Fusion

Olivér Törő

Tamás Bécsi

2022/12/5

Enhanced Experience Prioritization: A Novel Upper Confidence Bound Approach

IEEE Access

Bálint Kővári

Bálint Pelenczei

Tamás Bécsi

2023/12/4

Traffic Signal Control with Successor Feature-Based Deep Reinforcement Learning Agent

Electronics

Laszlo Szoke

Szilárd Aradi

Tamás Bécsi

2023/1

Reward design for intelligent intersection control to reduce emission

IEEE Access

Bálint Kővári

Bálint Pelenczei

Szilárd Aradi

Tamás Bécsi

2022/4/11

Monte Carlo Tree Search to Compare Reward Functions for Reinforcement Learning

Bálint Kövári

Bálint Pelenczei

Tamás Bécsi

2022/5/25

Multi-Agent Deep Reinforcement Learning (MADRL) for Solving Real-Time Railway Rescheduling Problem

Bálint Kővári

István Lövétei

Szilárd Aradi

Tamás Bécsi

2022

Milp-based optimization of the extended real-time railway traffic management problem

László Lindenmaier

Szilárd Aradi

Tamás Bécsi

István Ferenc Lövétei

2022/5/25

Double Lane Change Path Planning Using Reinforcement Learning with Field Tests

Árpád Fehér

Szilárd Aradi

Tamás Bécsi

2022

LPV-based modeling of a floating piston pneumatic actuator

Adam Szabo

Tamas Becsi

Szilard Aradi

2022/3/2

Environment representations of railway infrastructure for reinforcement learning-based traffic control

Applied Sciences

István Lövétei

Bálint Kővári

Tamás Bécsi

Szilárd Aradi

2022/4/28

Designing Reward Functions in Multi-Agent Reinforcement Learning for Intelligent Intersection Control

Máté Kolat

Bálint Kővári

Tamás Bécsi

Szilárd Aradi

2022/9/15

Deep reinforcement learning based approach for traffic signal control

Transportation Research Procedia

Kővári Bálint

Tettamanti Tamás

Bécsi Tamás

2022/1/1

See List of Professors in Tamás Bécsi University(Budapesti Muszaki és Gazdaságtudományi Egyetem)

Co-Authors

H-index: 26
Balazs Kulcsar

Balazs Kulcsar

Chalmers tekniska högskola

H-index: 22
Tamás Tettamanti

Tamás Tettamanti

Budapesti Muszaki és Gazdaságtudományi Egyetem

H-index: 22
István Varga

István Varga

Budapesti Muszaki és Gazdaságtudományi Egyetem

H-index: 20
Zsolt SZALAY

Zsolt SZALAY

Budapesti Muszaki és Gazdaságtudományi Egyetem

H-index: 19
Tamas Peter

Tamas Peter

Budapesti Muszaki és Gazdaságtudományi Egyetem

H-index: 14
Szilárd Aradi

Szilárd Aradi

Budapesti Muszaki és Gazdaságtudományi Egyetem

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