SUSTAINABLE DEVELOPMENT
Innovate. Sustain. Transform.
Save up to 30% on top Physical Sciences & Engineering titles!
Introduction to Intricate Artificial Psychology with Python
- 1st Edition - September 1, 2025
- Editors: Peter Watson, Hojjatollah Farahani, Timea Bezdan
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 3 0 2 4 8 - 0
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 3 0 2 4 9 - 7
Introduction to Intricate Artificial Psychology with Python unlocks the mysteries of Intricate Artificial Psychology (iAp). This comprehensive guide takes readers through advanc… Read more
Purchase options
Institutional subscription on ScienceDirect
Request a sales quoteIntroduction to Intricate Artificial Psychology with Python unlocks the mysteries of Intricate Artificial Psychology (iAp). This comprehensive guide takes readers through advanced cognitive frameworks and the complex landscape of artificial psychology using Python. Starting with an introduction to iAp, the book explores degrees of prediction and applies Fuzzy Cognitive Maps (IAP). Special focus is given to detecting implicit bias through a combination of Fuzzy Cognitive Maps and SHAP values, offering a unique perspective on artificial intelligence and psychological phenomena. The book covers forecasting in iAp, complex network analysis, and psychological graph analysis (Pga).
It delves into the intersection of deep learning and neuroimaging, as well as machine learning techniques in neuroimaging. It includes practical case studies, allowing readers to apply cutting-edge techniques to real-world psychological scenarios.
It delves into the intersection of deep learning and neuroimaging, as well as machine learning techniques in neuroimaging. It includes practical case studies, allowing readers to apply cutting-edge techniques to real-world psychological scenarios.
- Examines how to utilize and analyze predictive models and psychological graphs
- Illustrates how to apply machine learning and deep learning techniques in neuroimaging
- Includes specific code examples in Python
Researchers in psychology and cognitive neuroscience, and advanced biomedical engineering students
1. Introduction Intricate Artificial Psychology (iAp)
2. Towards Intricate Thinking
3. Prediction in Intricate Artificial Psychology
4. Fuzzy Cognitive Maps in Intricate Artificial Psychology (IAP
5. Detecting implicit bias using Fuzzy Cognitive Maps and SHAP values
6. Forecasting in Intricate Artificial Psychology
7. Explaining Predictive Models
8. Complex network Analysis
9. Psychological Graph Analysis (Pga)
10. Deep learning techniques in neuroimaging
11. Machine Learning techniques in neuroimaging
12. Becoming a PsychoPythonista
2. Towards Intricate Thinking
3. Prediction in Intricate Artificial Psychology
4. Fuzzy Cognitive Maps in Intricate Artificial Psychology (IAP
5. Detecting implicit bias using Fuzzy Cognitive Maps and SHAP values
6. Forecasting in Intricate Artificial Psychology
7. Explaining Predictive Models
8. Complex network Analysis
9. Psychological Graph Analysis (Pga)
10. Deep learning techniques in neuroimaging
11. Machine Learning techniques in neuroimaging
12. Becoming a PsychoPythonista
- No. of pages: 300
- Language: English
- Edition: 1
- Published: September 1, 2025
- Imprint: Academic Press
- Paperback ISBN: 9780443302480
- eBook ISBN: 9780443302497
PW
Peter Watson
Peter Watson holds three degrees in Mathematical Statistics including a Ph.D. (Manchester). He has been providing statistical support in various ways to the research at CBSU, the Cognition and Brain Sciences Unit in Cambridge (and its predecessor, the Applied Psychology Unit) since 1994 (and prior to that fulfilling a similar role at the MRC Age and Cognitive Performance Research Centre in Manchester). He is the co-author of over 100 papers and lectures at the University of Cambridge. He is a statistical referee for several journals including BMJ Open and the Journal of Affective Disorders. He has also been a major contributor of articles to the on-line CBSU statswiki web pages which receive upwards of 100,000 visits annually. He has also been secretary, since 1996, of the Cambridge Statistics Discussion Group and chair and meetings organiser for the SPSS users’ group (ASSESS) since 2001 and has also been a member of the Clinical Trials Advisory Panel for Alzheimer’s Research UK.
Affiliations and expertise
MRC Cognition and Brain Sciences Unit, University of Cambridge, UKHF
Hojjatollah Farahani
Hojjatollah Farahani is an Assistant Professor at the Tarbiat Modares University (TMU), Iran. He received his Ph.D. from Isfahan University in 2009, and he was a postdoctoral researcher in Fuzzy inference at the Victoria University in Australia (2014-2015), where he started working on Fuzzy Cognitive Maps (FCMs) under supervision of professor Yuan Miao. He is the author or co-author of more than 150 research papers and a reviewer in numerous scientific journals. He has supervised and advised many theses and dissertations in psychological sciences. His new book is “Introduction to artificial Psychology using R “which was published by Springer in 2023. His research interests and directions include psychometrics, fuzzy psychology, artificial intelligence, machine learning algorithms in psychology theoretical neuroscience, neurological pain, and trauma.
Affiliations and expertise
Tarbiat Modares University, IranTB
Timea Bezdan
Timea Bezdan is a Ph.D. candidate at the University Singidunum in Belgrade, Serbia, pursuing a doctoral degree in Computer Science. She works as a Teaching Assistant at the Technical Faculty and Faculty of Informatics and Computing within the same institution. Her principal research pursuits encompass optimization, swarm intelligence, machine learning, and artificial intelligence. Her scholarly contributions comprise over 40 published scientific papers, featured in esteemed journals and international conferences, all of which delve into these aforementioned domains.
Affiliations and expertise
University Singidunum, Serbia