國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Artificial psychologypsychological m...

Carbone, John.

Artificial psychologypsychological modeling and testing of AI systems /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Artificial psychologyby James A. Crowder, John Carbone, Shelli Friess.
其他題名:	psychological modeling and testing of AI systems /
作者:	Crowder, James A.
其他作者:	Carbone, John.
出版者:	Cham :Springer International Publishing :2020.
面頁冊數:	xvii, 169 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Artificial intelligencePsychological aspects.
電子資源:	https://doi.org/10.1007/978-3-030-17081-3
ISBN:	9783030170813$q(electronic bk.)

Artificial psychologypsychological modeling and testing of AI systems /
Crowder, James A.

Artificial psychologypsychological modeling and testing of AI systems /[electronic resource] :by James A. Crowder, John Carbone, Shelli Friess. - Cham :Springer International Publishing :2020. - xvii, 169 p. :ill. (some col.), digital ;24 cm.

Chapter 1. Introduction: Psychology and Technology -- Chapter 2. Systems-Level Thinking for Artificial Intelligent Systems -- Chapter 3. Psychological Constructs for AI Systems: The Information Continuum -- Chapter 4. Human-AI Collaboration -- Chapter 5. Abductive Artificial Intelligence Learning Models -- Chapter 6. Artificial Creativity and Self-Evolution: Abductive Reasoning in Artificial Life Forms -- Chapter 7. Artificial Intelligent Inferences utilizing Occam Abduction -- Chapter 8. Artificial Neural Diagnostics and Prognostics: Self-Soothing in Cognitive Systems -- Chapter 9. Ontology-Based Knowledge Management for Artificial Intelligent Systems -- Chapter 10. Cognitive Control of Self-Evolving Life Forms (SELF) utilizing Artificial Procedural Memories -- Chapter 11. Methodologies for Continuous, Life-Long Machine Learning for AI Systems -- Chapter 12. Implicit Learning in Artificial Intelligence -- Chapter 13. Data Analytics: The Big Data Analytics Process (BDAP) Architecture -- Chapter 14. Conclusions and Next Steps.

This book explores the subject of artificial psychology and how the field must adapt human neuro-psychological testing techniques to provide adequate cognitive testing of advanced artificial intelligence systems. It shows how classical testing methods will reveal nothing about the cognitive nature of the systems and whether they are learning, reasoning, and evolving correctly; for these systems, the authors outline how testing techniques similar to/adapted from human psychological testing must be adopted, particularly in understanding how the system reacts to failure or relearning something it has learned incorrectly or inferred incorrectly. The authors provide insights into future architectures/capabilities that artificial cognitive systems will possess and how we can evaluate how well they are functioning. It discusses at length the notion of human/AI communication and collaboration and explores such topics as knowledge development, knowledge modeling and ambiguity management, artificial cognition and self-evolution of learning, artificial brain components and cognitive architecture, and artificial psychological modeling. Explores the concepts of Artificial Psychology and Artificial Neuroscience as applied to advanced artificially cognitive systems; Provides insight into the world of cognitive architectures and biologically-based computing designs which will mimic human brain functionality in artificial intelligent systems of the future; Provides description and design of artificial psychological modeling to provide insight into how advanced artificial intelligent systems are learning and evolving; Explores artificial reasoning and inference architectures and the types of modeling and testing that will be required to "trust" an autonomous artificial intelligent systems.

ISBN: 9783030170813$q(electronic bk.)

Standard No.: 10.1007/978-3-030-17081-3doiSubjects--Topical Terms:

573014
Artificial intelligence
--Psychological aspects.

LC Class. No.: Q335 / .C76 2020

Dewey Class. No.: 006.3

Artificial psychologypsychological modeling and testing of AI systems /
LDR:03882nmm a2200325 a 4500 001 578144
003 DE-He213
005 20200211144749.0
006 m d
007 cr nn 008maaau
008 201208s2020 sz s 0 eng d
020 $a 9783030170813$q(electronic bk.)
020 $a 9783030170790$q(paper)
024 7 $a 10.1007/978-3-030-17081-3 $2 doi
035 $a 978-3-030-17081-3
040 $a GP $c GP
041 0 $a eng
050 4 $a Q335 $b .C76 2020
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
090 $a Q335 $b .C953 2020
100 1 $a Crowder, James A. $3 674864
245 1 0 $a Artificial psychology $h [electronic resource] : $b psychological modeling and testing of AI systems / $c by James A. Crowder, John Carbone, Shelli Friess.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xvii, 169 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a Chapter 1. Introduction: Psychology and Technology -- Chapter 2. Systems-Level Thinking for Artificial Intelligent Systems -- Chapter 3. Psychological Constructs for AI Systems: The Information Continuum -- Chapter 4. Human-AI Collaboration -- Chapter 5. Abductive Artificial Intelligence Learning Models -- Chapter 6. Artificial Creativity and Self-Evolution: Abductive Reasoning in Artificial Life Forms -- Chapter 7. Artificial Intelligent Inferences utilizing Occam Abduction -- Chapter 8. Artificial Neural Diagnostics and Prognostics: Self-Soothing in Cognitive Systems -- Chapter 9. Ontology-Based Knowledge Management for Artificial Intelligent Systems -- Chapter 10. Cognitive Control of Self-Evolving Life Forms (SELF) utilizing Artificial Procedural Memories -- Chapter 11. Methodologies for Continuous, Life-Long Machine Learning for AI Systems -- Chapter 12. Implicit Learning in Artificial Intelligence -- Chapter 13. Data Analytics: The Big Data Analytics Process (BDAP) Architecture -- Chapter 14. Conclusions and Next Steps.
520 $a This book explores the subject of artificial psychology and how the field must adapt human neuro-psychological testing techniques to provide adequate cognitive testing of advanced artificial intelligence systems. It shows how classical testing methods will reveal nothing about the cognitive nature of the systems and whether they are learning, reasoning, and evolving correctly; for these systems, the authors outline how testing techniques similar to/adapted from human psychological testing must be adopted, particularly in understanding how the system reacts to failure or relearning something it has learned incorrectly or inferred incorrectly. The authors provide insights into future architectures/capabilities that artificial cognitive systems will possess and how we can evaluate how well they are functioning. It discusses at length the notion of human/AI communication and collaboration and explores such topics as knowledge development, knowledge modeling and ambiguity management, artificial cognition and self-evolution of learning, artificial brain components and cognitive architecture, and artificial psychological modeling. Explores the concepts of Artificial Psychology and Artificial Neuroscience as applied to advanced artificially cognitive systems; Provides insight into the world of cognitive architectures and biologically-based computing designs which will mimic human brain functionality in artificial intelligent systems of the future; Provides description and design of artificial psychological modeling to provide insight into how advanced artificial intelligent systems are learning and evolving; Explores artificial reasoning and inference architectures and the types of modeling and testing that will be required to "trust" an autonomous artificial intelligent systems.
650 0 $a Artificial intelligence $x Psychological aspects. $3 573014
650 1 4 $a Computational Intelligence. $3 338479
650 2 4 $a Artificial Intelligence. $3 212515
650 2 4 $a User Interfaces and Human Computer Interaction. $3 274517
650 2 4 $a Neurosciences. $3 211508
650 2 4 $a Behavioral Therapy. $3 273860
700 1 $a Carbone, John. $3 866743
700 1 $a Friess, Shelli. $3 710488
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-3-030-17081-3
950 $a Intelligent Technologies and Robotics (Springer-42732)