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Adaptive Behavior
基本信息
期刊名称 Adaptive Behavior
ADAPT BEHAV
期刊ISSN 1059-7123
期刊官方网站 https://journals.sagepub.com/home/ADB
是否OA No
出版商 SAGE Publications Ltd
出版周期 Bimonthly
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始发年份 1992
年文章数 34
影响因子 1.2(2023)  scijournal影响因子  greensci影响因子
中科院SCI期刊分区
大类学科 小类学科 Top 综述
工程技术4区 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机:人工智能4区
CiteScore
CiteScore排名 CiteScore SJR SNIP
学科 排名 百分位 4.3 0.562 0.866
Psychology
Experimental and Cognitive Psychology
57/165 65%
Neuroscience
Behavioral Neuroscience
49/88 44%
补充信息
自引率 25%
H-index 47
SCI收录状况 Science Citation Index Expanded
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PubMed Central (PMC) http://www.ncbi.nlm.nih.gov/nlmcatalog?term=1059-7123%5BISSN%5D
投稿指南
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The study and simulation of adaptive behavior in natural and artificial systems has always involved the convergence of several disciplines, interests, and methods. Since its inception in 1992, the pages of this journal have reflected a cross-fertilization between the sciences of the artificial, the sciences of living systems, and the sciences of the mind. As a result, Adaptive Behavior has been, and continues to be, a forum for innovative, creative, yet rigorous and peer-reviewed work on complex adaptive systems, robotic and computational investigations of behavior and cognition, as well as novel theoretical developments and applications.

The general mission of Adaptive Behavior has not changed fundamentally even as the journal, like any good adaptive system, assimilates and accommodates to new challenges and open questions. Accordingly, our particular aims are constantly on the move, as they are driven no only by general advances in knowledge, as occurs within any well-defined research discipline, but also by the birth of new research programs out of the stimulating intellectual milieu of interdisciplinary debate and collaboration. A key purpose of this journal is to facilitate such creative work by being the source of new ideas, the forum for novel recombination, and a place to ask difficult questions that are rarely asked at the core of individual disciplines.

Realizing these goals means encouraging high-quality publications and debate in several exciting and emerging research areas. In particular, the journal aims to contribute to the consolidation of new approaches to cognitive science, especially research related to the consolidation of new approaches to cognitive science, especially research related to "4E cognition" (embodied, embedded, extended, and enactive cognition), including the predictive coding framework, autopoietic and sensorimotor theory, as well as dynamical and ecological approaches to psychology. This journal is equally a fitting home for expanding research on the possibilities of intelligence without a central nervous system, such as behavior-based approaches to the origin of life, plant cognition and the adaptive capacities of multi-agent and social systems. Another important area is living technology, which includes morphological computation, deep neural networks, soft robotics, and other advances in the methods and practical applications of bio-inspired robotics and self-optimization. 

In particular, we identify the following research challenges:

- To better understand the adaptive and cognitive capacities of (bio-)chemical systems
- To concretize predictive coding into a framework that can be more easily applied to advancing actual examples of cognitive robotics
- To replicate biological autonomy in artificial systems (or to demonstrate why this cannot be done)
- To determine whether the various new approaches to the science of mind are compatible or, alternatively, to determine their competing predictions
- To better understand what (if any) are the limits of intelligence without a nervous system and intelligence without representations
- To clarify the nature of the normativity inherent in living systems in such a way that it could improve cognitive robotics and living technology
- To better understand the conditions under which multi-agent and social systems generate collective properties that benefit their components
- To search for new materials that allow for more adaptive robot bodies

Contributions that address one or more of these research challenges are particularly welcomed. 


Submissions from the general area of machine learning will be returned without review unless the findings have clear scientific relevance.
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Editor in Chief

Tom Froese

Assistant Professor, Okinawa Institute of Science and Technology, Japan

Associate Editors

Eran Agmon

Columbia University, USA

Alberto Antonioni

University College London, UK

Nathaniel Barrett

University of Navarra, Spain

Manuel G. Bedia

University of Zaragoza, Spain

Joost Broekens

Delft University of Technology, Netherlands

Dr Massimiliano Cappuccio

University of New South Wales, Australia

Luisa Damiano

University of Messina, Italy

Ezequiel Di Paolo

University of the Basque Country, Spain

James A. Dixon

University of Connecticut, USA

Dobromir Dotov

McMaster University, Canada

Dr Guillaume Dumas

Institut Pasteur, France

Ángel E. Tovar

National Autonomous University of Mexico, Mexico

Matthew Egbert

University of Auckland, New Zealand

Verena V. Hafner

Humboldt-Universität zu Berlin, Germany

Martin Michael Hanczyc

Università degli Studi di Trento, Italy

Matej Hoffmann

Czech Technical University, Prague

Hiroyuki Iizuka

Hokkaido University, Japan

Eduardo J. Izquierdo

Indiana University, USA

Michael Kirchhoff

University of Wollongong, Australia

Bruno Lara

Autonomous University of the State of Morelos (UAEM), Mexico

Tom Lenaerts

Université Libre de Bruxelles, Belgium?

Lorena Lobo

Universidad a Distancia de Madrid, Spain

Robert Lowe

University of Gothenburg, Sweden

Poramate Manoonpong

University of Southern Denmark, Denmark

Georg Martius

Max Planck Institute for Intelligent Systems, Germany

Marek McGann

University of Limerick, Ireland

Geoff Nitschke

University of Cape Town, South Africa

Jekaterina Novikova

Heriot-Watt University, UK

Andrew Philippides

University of Sussex, UK

Simon T. Powers

Edinburgh Napier University, UK

Etienne Roesch

University of Reading, UK

Erol Sahin

Middle East Technical University, Turkey

Christoph Salge

University of Hertfordshire, UK

Francisco C. Santos

IST, Universidade de Lisboa, Portugal

Jeffrey Schank

University of California (UC Davis), USA

Pierre Steiner

Université de Technologie de Compiègne, France

Serge Thill

Donders Institute for Brain, Cognition, and Behaviour, Netherlands

Patricia A. Vargas

Heriot-Watt University, UK

Mario Villalobos

Universidad de Tarapacá, Arica, Chile

Myra S Wilson

Aberystwyth University, UK

Philipp Zech

University of Innsbruck, Austria

Editorial Board

David H. Ackley

University of New Mexico, USA

Michael Arbib

University of Southern California, USA

Andrew Barto

University of Massachusetts, USA

Randall D. Beer

Indiana University, USA

Rodney A Brooks

Massachusetts Institute of Technology, USA

Joanna J Bryson

University of Bath, UK

Seth Bullock

University of Bristol, UK

Holk Cruse

University of Bielefeld, Germany

Kerstin Dautenhahn

University of Hertfordshire, UK

Daniel Dennett

Tufts University, USA

Marco Dorigo

Université Libre de Bruxelles, Belgium

Kenji Doya

Okinawa Institute of Science and Technology, Japan

Jörg-Peter Ewert

University of Kassel, Germany

Dario Floreano

Swiss Fed. Inst. of Technology (EPFL), Lausanne, Switzerland

Nicolas Franceschini

Centre National de la Recherche Scientifique (CNRS), France

David E. Goldberg

University of Illinois at Urbana - Champaign, USA

John Grefenstette

George Mason University, USA

Stephen Grossberg

Boston University, USA

John Hallam

University of Southern Denmark, Denmark

Inman Harvey

University of Sussex, UK

Phil Husbands

University of Sussex, UK

Daniel D. Hutto

University of Wollongong, Australia

Auke Jan Ijspeert

Ecole Polytechnique Fédérale de Lausanne, Switzerland

Takashi Ikegami

University of Tokyo, Japan

Jean-Arcady Meyer

Institute for Intelligent Systems and Robotics (ISIR), France

Alvaro Moreno

University of the Basque Country (UPV/EHU), Spain

Stefano Nolfi

Institute of Cognitive Sciences and Technologies (CNR-ISTC), Italy

Frank Pasemann

Osnabrück University, Germany

Rolf Pfeifer

Osaka University, Japan

Herbert L. Roitblat

Mimecast, USA

J.A. Scott Kelso

Florida Atlantic University & Ulster University,USA and Ireland

Olaf Sporns

Indiana University, USA

Luc Steels

Vrij Universiteit Brussels (VUB), Belgium

Prof. Jun Tani

Okinawa Institute of Science and Technology, Japan

Frederick M. Toates

The Open University, UK

Peter M Todd

Indiana University, USA

Barbara Webb

University of Edinburgh, UK

Stewart W. Wilson

Prediction Dynamics, USA


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