Application of AI based reinforcement learning to robot vehicle control

M. G.M. Madden; P. J. Nolan

Application of AI based reinforcement learning to robot vehicle control

M. G.M. Madden, P. J. Nolan

Mechanical Engineering

University of Galway

Research output: Contribution to conference (Published) › Paper › peer-review

2 Citations (Scopus)

Abstract

Reinforcement learning is a form of artificial intelligence in which an agent acquires and improves skills based on receiving positive and negative rewards when it performs actions within an environment. This paper describes a system which uses an extended reinforcement learning algorithm to generate reactive control strategies. It is applied to the control of a vehicle in a simulated traffic environment.

Original language	English
Pages	437-445
Number of pages	9
Publication status	Published - 1995
Event	Proceedings of the 1995 10th International Conference on Applications of Artificial Intelligence in Engineering, AIENG'95 - Udine, Italy Duration: 1 Jul 1995 → 1 Jul 1995

Conference

Conference	Proceedings of the 1995 10th International Conference on Applications of Artificial Intelligence in Engineering, AIENG'95
City	Udine, Italy
Period	1/07/95 → 1/07/95

Cite this

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title = "Application of AI based reinforcement learning to robot vehicle control",

abstract = "Reinforcement learning is a form of artificial intelligence in which an agent acquires and improves skills based on receiving positive and negative rewards when it performs actions within an environment. This paper describes a system which uses an extended reinforcement learning algorithm to generate reactive control strategies. It is applied to the control of a vehicle in a simulated traffic environment.",

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year = "1995",

language = "English",

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note = "Proceedings of the 1995 10th International Conference on Applications of Artificial Intelligence in Engineering, AIENG'95 ; Conference date: 01-07-1995 Through 01-07-1995",

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AU - Madden, M. G.M.

AU - Nolan, P. J.

PY - 1995

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AB - Reinforcement learning is a form of artificial intelligence in which an agent acquires and improves skills based on receiving positive and negative rewards when it performs actions within an environment. This paper describes a system which uses an extended reinforcement learning algorithm to generate reactive control strategies. It is applied to the control of a vehicle in a simulated traffic environment.

UR - https://www.scopus.com/pages/publications/0029454044

M3 - Paper

AN - SCOPUS:0029454044

SP - 437

EP - 445

T2 - Proceedings of the 1995 10th International Conference on Applications of Artificial Intelligence in Engineering, AIENG'95

Y2 - 1 July 1995 through 1 July 1995

ER -

Application of AI based reinforcement learning to robot vehicle control

Abstract

Conference

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