Birth of intelligence : from RNA to artificial intelligence

著者

    • Lee, Daeyeol

書誌事項

Birth of intelligence : from RNA to artificial intelligence

Daeyeol Lee

Oxford University Press, c2020

  • : hbk

大学図書館所蔵 件 / 全4件

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

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.

目次

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

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