BIRTH OF INTELLIGENCE C

Erscheinungsjahr 2020
ISBN: 978-0-19-090832-4
Verlag: ACADEMIC

Buch, Englisch, 232 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 520 g

What is intelligence? How did it begin and evolve to human intelligence? Does a high level of biological intelligence require a complex brain? Can man-made machines be truly intelligent? Is AI fundamentally different from human intelligence? In Birth of Intelligence, distinguished neuroscientist Daeyeol Lee tackles these pressing fundamental issues. To better prepare for future society and its technology, including how the use of AI will impact our lives, it is essential to understand the biological root and limits of human intelligence. After systematically reviewing biological and computational underpinnings of decision making and intelligent behaviors, Birth of Intelligence proposes that true intelligence requires life.

Autoren/Hrsg.

Lee

Lee, Daeyeol

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Sozialwissenschaften Psychologie Allgemeine Psychologie Kognitionspsychologie

Inhaltsverzeichnis

- Preface

- Chapter 1. Levels of Intelligence

- What is Intelligence?

- Intelligence without neurons: bacteria to plants

- How does a nervous system work?

- Reflexes: simple behavior

- Limitations of reflexes

- Connectome

- Multiple controllers for muscles

- Eye movements: a case study

- Many behaviors are social

- Chapter 2. Brain and Decision Making

- Utility theory

- Time and uncertainty

- Indecision: Buridan's ass

- Limitations of the utility theory

- Happiness

- Utility theory and the brain

- Meaning of action potentials

- Evolution of utilities

- Chapter 3. Artificial Intelligence

- Brain versus computer

- Will computers outperform human brains

- Synapse vs. transistor

- Hardware vs. software

- AI on Mars

- Is Sojourner still alive?

- Autonomous AI

- AI and utilities

- Robot society and swarm intelligence

- Chapter 4. Self-replicating machine

- Self-replicating machines

- Natural history of self-replicating machines

- Multi-talented proteins

- Multicellular organisms

- Brain evolution

- Evolution and Development

- Chapter 5. Brain and Genes

- Division of labor and delegation

- Principal-agent relationship

- Brain's incentive

- Chapter 6. Why learning?

- Diversity of learning

- Classical conditioning: a salivating dog

- Law of effect and instrumental conditioning: a curious cat

- Instrumental meets classical

- Instrumental and classical clash

- Knowledge: latent learning and place learning

- Chapter 7. Brain for Learning

- Neurons and learning

- Search for the engram

- Hippocampus and basal ganglia

- Reinforcement learning theory

- Pleasure chemical: dopamine

- Reinforcement learning and knowledge

- Regret and orbitofrontal cortex

- Regret neurons

- Chapter 8. Social Intelligence and Altruism

- Game theory

- Death of game theory?

- Iterative prisoner's dilemma

- Pavlov strategy

- Cooperating society

- Dark side of altruism

- Predicting the behaviors of others

- Recursive mind

- Social brain

- Default cognition: anthropomorphization

- Chapter 9. Intelligence and Self

- Paradox of self-knowledge

- Meta-cognition and meta-selection

- Cost of intelligence

- Chapter 10. Conclusion: Questions for Artificial Intelligence

Über Autor(innen)

Daeyeol Lee received his undergraduate degree in economics from Seoul National University in South Korea, and his doctoral degree in neuroscience from the University of Illinois at Urbana-Champaign in the United States. He has held faculty appointments at Wake Forest University, University of Rochester, and Yale University, before joining the Zanvyl Krieger Mind/Brain Institute at the Johns Hopkins University as a Bloomberg Distinguished Professor in 2019. His research focuses on the brain mechanisms of decision making and high-level cognition.