Example of Adaptive Behavior format
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Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format
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Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format Example of Adaptive Behavior format
Sample paper formatted on SciSpace - SciSpace
This content is only for preview purposes. The original open access content can be found here.
open access Open Access
recommended Recommended

Adaptive Behavior — Template for authors

Publisher: SAGE
Categories Rank Trend in last 3 yrs
Philosophy #35 of 644 down down by None rank
Experimental and Cognitive Psychology #87 of 148 down down by 4 ranks
Artificial Intelligence #142 of 227 down down by None rank
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 103 Published Papers | 247 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 02/07/2020
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Related Journals

open access Open Access
recommended Recommended

Springer

Quality:  
High
CiteRatio: 4.4
SJR: 0.806
SNIP: 2.211
open access Open Access
recommended Recommended

Elsevier

Quality:  
High
CiteRatio: 5.7
SJR: 2.223
SNIP: 2.098
open access Open Access

Elsevier

Quality:  
High
CiteRatio: 6.0
SJR: 0.52
SNIP: 1.569
open access Open Access
recommended Recommended

Elsevier

Quality:  
High
CiteRatio: 7.7
SJR: 2.442
SNIP: 2.279

Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

0.929

32% from 2018

Impact factor for Adaptive Behavior from 2016 - 2019
Year Value
2019 0.929
2018 1.362
2017 1.0
2016 1.019
graph view Graph view
table view Table view

2.4

14% from 2019

CiteRatio for Adaptive Behavior from 2016 - 2020
Year Value
2020 2.4
2019 2.8
2018 2.6
2017 2.3
2016 2.7
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has decreased by 32% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has decreased by 14% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

0.286

9% from 2019

SJR for Adaptive Behavior from 2016 - 2020
Year Value
2020 0.286
2019 0.315
2018 0.345
2017 0.288
2016 0.454
graph view Graph view
table view Table view

0.689

0% from 2019

SNIP for Adaptive Behavior from 2016 - 2020
Year Value
2020 0.689
2019 0.691
2018 0.837
2017 0.607
2016 0.763
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has decreased by 9% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has decreased by 0% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

Adaptive Behavior

Guideline source: View

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SAGE

Adaptive Behavior

Adaptive Behavior is a highly ranked, international peer reviewed journal that publishes original research and review articles on adaptive behavior in living organisms and autonomous artificial systems. For over 17 years it has offered ethologists, psychologists, behavioral ec...... Read More

Psychology

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Last updated on
01 Jul 2020
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ISSN
1059-7123
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Impact Factor
High - 1.164
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Open Access
No
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Sherpa RoMEO Archiving Policy
Green faq
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Plagiarism Check
Available via Turnitin
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Endnote Style
Download Available
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Bibliography Name
SageV
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Citation Type
Author Year
(Blonder et al., 1982)
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Bibliography Example
Blonder, G. E., Tinkham, M., and Klapwijk, T. M. (1982). Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and super- current conversion. Phys. Rev. B, 25(7):4515–4532.

Top papers written in this journal

Journal Article DOI: 10.1177/105971239700500203
Ant-based load balancing in telecommunications networks
Ruud Schoonderwoerd1, Janet Bruten2, Owen Holland3, Léon J. M. Rothkrantz1
01 Sep 1996 - Adaptive Behavior

Abstract:

This article describes a novel method of achieving load balancing in telecommunications networks. A simulated network models a typical distribution of calls between nodes; nodes carrying an excess ... This article describes a novel method of achieving load balancing in telecommunications networks. A simulated network models a typical distribution of calls between nodes; nodes carrying an excess ... read more read less

Topics:

Load balancing (computing) (66%)66% related to the paper, Loss network (58%)58% related to the paper, Telecommunications network (57%)57% related to the paper, Network model (50%)50% related to the paper
838 Citations
Journal Article DOI: 10.1177/105971239200100105
Evolving dynamical neural networks for adaptive behavior
Randall D. Beer1, John C. Gallagher1
30 Jun 1992 - Adaptive Behavior

Abstract:

We would like the behavior of the artificial agents that we construct to be as well-adapted to their environments as natural animals are to theirs. Unfortunately, designing controllers with these properties is a very difficult task. In this article, we demonstrate that continuous-time recurrent neural networks are a viable me... We would like the behavior of the artificial agents that we construct to be as well-adapted to their environments as natural animals are to theirs. Unfortunately, designing controllers with these properties is a very difficult task. In this article, we demonstrate that continuous-time recurrent neural networks are a viable mechanism for adaptive agent control and that the genetic algorithm can be used to evolve effective neural controllers. A significant advantage of this approach is that one need specify only a measure of an agent's overall performance rather than the precise motor output trajectories by which it is achieved. By manipulating the performance evaluation, one can place selective pressure on the development of controllers with desired properties. Several novel controllers have been evolved, including a chemotaxis controller that switches between different strategies depending on environmental conditions, and a locomotion controller that takes advantage of sensory feedback if available but th... read more read less

Topics:

Control theory (56%)56% related to the paper, Time delay neural network (55%)55% related to the paper, Recurrent neural network (54%)54% related to the paper, Artificial neural network (52%)52% related to the paper, Adaptive behavior (51%)51% related to the paper
561 Citations
Journal Article DOI: 10.1177/105971239700500305
Incremental Evolution of Complex General Behavior
Faustino Gomez1, Risto Mikkulainen1
01 Jan 1997 - Adaptive Behavior

Abstract:

Several researchers have demonstrated how complex action sequences can be learned through neuroevolution (i.e., evolving neural networks with genetic algorithms). However, complex general behavior such as evading predators or avoiding obstacles, which is not tied to specific environments, turns out to be very difficult to evo... Several researchers have demonstrated how complex action sequences can be learned through neuroevolution (i.e., evolving neural networks with genetic algorithms). However, complex general behavior such as evading predators or avoiding obstacles, which is not tied to specific environments, turns out to be very difficult to evolve. Often the system discovers mechanical strategies, such as moving back and forth, that help the agent cope but are not very effective, do not appear believable, and do not generalize to new environments. The problem is that a general strategy is too difficult for the evolution system to discover directly. This article proposes an approach wherein such complex general behavior is learned incrementally, by starting with simpler behavior and gradually making the task more challenging and general. The task transitions are implemented through successive stages of Delta coding (i.e., evolving modifications), which allows even converged populations to adapt to the new task. The method is... read more read less

Topics:

Neuroevolution (57%)57% related to the paper, Task (project management) (50%)50% related to the paper
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473 Citations
Journal Article DOI: 10.1177/1059712303114001
The Dynamics of Active Categorical Perception in an Evolved Model Agent
Randall D. Beer1
01 Dec 2003 - Adaptive Behavior

Abstract:

Notions of embodiment, situatedness, and dynamics are increasingly being debated in cognitive sci ence. However, these debates are often carried out in the absence of concrete examples. In order to... Notions of embodiment, situatedness, and dynamics are increasingly being debated in cognitive sci ence. However, these debates are often carried out in the absence of concrete examples. In order to... read more read less
460 Citations
open accessOpen access Journal Article DOI: 10.1177/105971230501300301
Reinforcement learning for RoboCup soccer keepaway
Peter Stone1, Richard S. Sutton2, Gregory Kuhlmann1
01 Sep 2005 - Adaptive Behavior

Abstract:

RoboCup simulated soccer presents many challenges to reinforcement learning methods, including a large state space, hidden and uncertain state, multiple independent agents learning simultaneously, and long and variable delays in the effects of actions. We describe our application of episodic SMDP Sarsa(λ) with linear tile-cod... RoboCup simulated soccer presents many challenges to reinforcement learning methods, including a large state space, hidden and uncertain state, multiple independent agents learning simultaneously, and long and variable delays in the effects of actions. We describe our application of episodic SMDP Sarsa(λ) with linear tile-coding function approximation and variable λ to learning higher-level decisions in a keepaway subtask of RoboCup soccer. In keepaway, one team, “the keepers,” tries to keep control of the ball for as long as possible despite the efforts of “the takers.” The keepers learn individually when to hold the ball and when to pass to a teammate. Our agents learned policies that significantly outperform a range of benchmark policies. We demonstrate the generality of our approach by applying it to a number of task variations including different field sizes and different numbers of players on each team. read more read less

Topics:

Reinforcement learning (54%)54% related to the paper
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430 Citations
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With SciSpace, you do not need a word template for Adaptive Behavior.

It automatically formats your research paper to SAGE formatting guidelines and citation style.

You can download a submission ready research paper in pdf, LaTeX and docx formats.

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Time taken to format a paper and Compliance with guidelines

Plagiarism Reports via Turnitin

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Adaptive Behavior format uses SageV citation style.

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Frequently asked questions

1. Can I write Adaptive Behavior in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Adaptive Behavior guidelines and auto format it.

2. Do you follow the Adaptive Behavior guidelines?

Yes, the template is compliant with the Adaptive Behavior guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Adaptive Behavior?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Adaptive Behavior citation style.

4. Can I use the Adaptive Behavior templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Adaptive Behavior.

5. Can I use a manuscript in Adaptive Behavior that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Adaptive Behavior that you can download at the end.

6. How long does it usually take you to format my papers in Adaptive Behavior?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Adaptive Behavior.

7. Where can I find the template for the Adaptive Behavior?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Adaptive Behavior's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Adaptive Behavior's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Adaptive Behavior an online tool or is there a desktop version?

SciSpace's Adaptive Behavior is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Adaptive Behavior?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Adaptive Behavior?”

11. What is the output that I would get after using Adaptive Behavior?

After writing your paper autoformatting in Adaptive Behavior, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Adaptive Behavior's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Adaptive Behavior?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Adaptive Behavior. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Adaptive Behavior?

The 5 most common citation types in order of usage for Adaptive Behavior are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Adaptive Behavior?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Adaptive Behavior's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Adaptive Behavior in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Adaptive Behavior Endnote style according to Elsevier guidelines.

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I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

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