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You searched for subject:(opposition based learning). Showing records 1 – 5 of 5 total matches.

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1. CHONG JIN KIAT. EVOLUTIONARY MULTI-OBJECTIVE OPTIMIZATION VIA DIFFERENTIAL EVOLUTION.

Degree: 2015, National University of Singapore

Subjects/Keywords: Multi-objective optimization; differential evolution; evolutionary algorithms; opposition-based learning; self-adaptation; memetic algorithms

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

KIAT, C. J. (2015). EVOLUTIONARY MULTI-OBJECTIVE OPTIMIZATION VIA DIFFERENTIAL EVOLUTION. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/122843

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

KIAT, CHONG JIN. “EVOLUTIONARY MULTI-OBJECTIVE OPTIMIZATION VIA DIFFERENTIAL EVOLUTION.” 2015. Thesis, National University of Singapore. Accessed August 08, 2020. http://scholarbank.nus.edu.sg/handle/10635/122843.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

KIAT, CHONG JIN. “EVOLUTIONARY MULTI-OBJECTIVE OPTIMIZATION VIA DIFFERENTIAL EVOLUTION.” 2015. Web. 08 Aug 2020.

Vancouver:

KIAT CJ. EVOLUTIONARY MULTI-OBJECTIVE OPTIMIZATION VIA DIFFERENTIAL EVOLUTION. [Internet] [Thesis]. National University of Singapore; 2015. [cited 2020 Aug 08]. Available from: http://scholarbank.nus.edu.sg/handle/10635/122843.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

KIAT CJ. EVOLUTIONARY MULTI-OBJECTIVE OPTIMIZATION VIA DIFFERENTIAL EVOLUTION. [Thesis]. National University of Singapore; 2015. Available from: http://scholarbank.nus.edu.sg/handle/10635/122843

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Ontario Institute of Technology

2. Esmailzadeh, Ali. Novel opposition-based sampling methods for efficiently solving challenging optimization problems.

Degree: 2011, University of Ontario Institute of Technology

 In solving noise-free and noisy optimization problems, candidate initialization and sampling play a key role, but are not deeply investigated. It is of interest to… (more)

Subjects/Keywords: Opposition-based learning; Large-scale; Noisy; Sampling methods; Evolutionary algorithm

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Esmailzadeh, A. (2011). Novel opposition-based sampling methods for efficiently solving challenging optimization problems. (Thesis). University of Ontario Institute of Technology. Retrieved from http://hdl.handle.net/10155/150

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Esmailzadeh, Ali. “Novel opposition-based sampling methods for efficiently solving challenging optimization problems.” 2011. Thesis, University of Ontario Institute of Technology. Accessed August 08, 2020. http://hdl.handle.net/10155/150.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Esmailzadeh, Ali. “Novel opposition-based sampling methods for efficiently solving challenging optimization problems.” 2011. Web. 08 Aug 2020.

Vancouver:

Esmailzadeh A. Novel opposition-based sampling methods for efficiently solving challenging optimization problems. [Internet] [Thesis]. University of Ontario Institute of Technology; 2011. [cited 2020 Aug 08]. Available from: http://hdl.handle.net/10155/150.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Esmailzadeh A. Novel opposition-based sampling methods for efficiently solving challenging optimization problems. [Thesis]. University of Ontario Institute of Technology; 2011. Available from: http://hdl.handle.net/10155/150

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

3. Malisia, Alice Ralickas. Investigating the Application of Opposition-Based Ideas to Ant Algorithms.

Degree: 2007, University of Waterloo

Opposition-based learning (OBL) was recently proposed to extend di erent machine learning algorithms. The main idea of OBL is to consider opposite estimates, actions or… (more)

Subjects/Keywords: ant colony optimization; opposition-based learning; machine learning; ant colony system; ant system; OBL; ant algorithm

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Malisia, A. R. (2007). Investigating the Application of Opposition-Based Ideas to Ant Algorithms. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/3233

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Malisia, Alice Ralickas. “Investigating the Application of Opposition-Based Ideas to Ant Algorithms.” 2007. Thesis, University of Waterloo. Accessed August 08, 2020. http://hdl.handle.net/10012/3233.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Malisia, Alice Ralickas. “Investigating the Application of Opposition-Based Ideas to Ant Algorithms.” 2007. Web. 08 Aug 2020.

Vancouver:

Malisia AR. Investigating the Application of Opposition-Based Ideas to Ant Algorithms. [Internet] [Thesis]. University of Waterloo; 2007. [cited 2020 Aug 08]. Available from: http://hdl.handle.net/10012/3233.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Malisia AR. Investigating the Application of Opposition-Based Ideas to Ant Algorithms. [Thesis]. University of Waterloo; 2007. Available from: http://hdl.handle.net/10012/3233

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

4. Shokri, Maryam. Oppositional Reinforcement Learning with Applications.

Degree: 2008, University of Waterloo

 Machine intelligence techniques contribute to solving real-world problems. Reinforcement learning (RL) is one of the machine intelligence techniques with several characteristics that make it suitable… (more)

Subjects/Keywords: Reinforcement learning; opposition-based learning; OQ(lambda); NOQ(lambda)

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Shokri, M. (2008). Oppositional Reinforcement Learning with Applications. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/4040

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Shokri, Maryam. “Oppositional Reinforcement Learning with Applications.” 2008. Thesis, University of Waterloo. Accessed August 08, 2020. http://hdl.handle.net/10012/4040.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Shokri, Maryam. “Oppositional Reinforcement Learning with Applications.” 2008. Web. 08 Aug 2020.

Vancouver:

Shokri M. Oppositional Reinforcement Learning with Applications. [Internet] [Thesis]. University of Waterloo; 2008. [cited 2020 Aug 08]. Available from: http://hdl.handle.net/10012/4040.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Shokri M. Oppositional Reinforcement Learning with Applications. [Thesis]. University of Waterloo; 2008. Available from: http://hdl.handle.net/10012/4040

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Waterloo

5. Rahnamayan, Shahryar. Opposition-Based Differential Evolution.

Degree: 2007, University of Waterloo

 Evolutionary algorithms (EAs) are well-established techniques to approach those problems which for the classical optimization methods are difficult to solve. Tackling problems with mixed-type of… (more)

Subjects/Keywords: Differential Evolution; Optimization; Evolutionary Algorithms; Opposition-Based Learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Rahnamayan, S. (2007). Opposition-Based Differential Evolution. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/2784

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Rahnamayan, Shahryar. “Opposition-Based Differential Evolution.” 2007. Thesis, University of Waterloo. Accessed August 08, 2020. http://hdl.handle.net/10012/2784.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Rahnamayan, Shahryar. “Opposition-Based Differential Evolution.” 2007. Web. 08 Aug 2020.

Vancouver:

Rahnamayan S. Opposition-Based Differential Evolution. [Internet] [Thesis]. University of Waterloo; 2007. [cited 2020 Aug 08]. Available from: http://hdl.handle.net/10012/2784.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Rahnamayan S. Opposition-Based Differential Evolution. [Thesis]. University of Waterloo; 2007. Available from: http://hdl.handle.net/10012/2784

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.