Adaptive Behavior

Aims & Scope

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.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	1.3
2024	1.20

SJR (SCImago Journal Rank)

Year	Value
2024	0.413

Quartile

Year	Value
2024	Q1

Journal Rank

Year	Value
2024	13478

Journal Citation Indicator

Year	Value
2024	239

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Arts and Humanities, Computer Science, Neuroscience and Psychology, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Ant-Based Load Balancing in Telecommunications Networks

  Citation: 443

  Authors: Ruud, Owen E., Janet L., Leon J. M.

• Evolving Dynamical Neural Networks for Adaptive Behavior

  Citation: 353

  Authors: Randall D., John C.

• The Dynamics of Active Categorical Perception in an Evolved Model Agent

  Citation: 310

  Authors: Randall D.

• Incremental Evolution of Complex General Behavior

  Citation: 275

  Authors: Faustino, Risto

• Defining Agency: Individuality, Normativity, Asymmetry, and Spatio-temporality in Action

  Citation: 274

  Authors: Xabier E., Ezequiel, Marieke

• On the Dynamics of Small Continuous-Time Recurrent Neural Networks

  Citation: 263

  Authors: Randall D.

• Explorations in Evolutionary Robotics

  Citation: 254

  Authors: Dave, Phil, Inman

• Collective Robotics: From Social Insects to Robots

  Citation: 231

  Authors: C. Ronald

• Reinforcement Learning for RoboCup Soccer Keepaway

  Citation: 225

  Authors: Peter, Richard S., Gregory

• To Afford or Not to Afford: A New Formalization of Affordances Toward Affordance-Based Robot Control

  Citation: 223

  Authors: Erol, Maya, Mehmet R., Emre, Göktürk

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