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汪军_A Theory of AI Agent_watermark.pdf

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1、On the Physical Foundation On the Physical Foundation of AI Agentsof AI AgentsJun Wang,UCLJun.wangcs.ucl.ac.ukTable of contentsTable of contents What is AI agent AI agent as a system Maxwells demon and energy bound for AI agents A simple example ConclusionsLearning Learning a agentgent In biology,le

2、arning means a change of behaviour as a result of experience In classical conditioning1,animals can learn to identify a useful pattern in the environment by associating onestimulus with another:repeated given ring-a-bell O,food X,a dog will start to salivate(anticipate the upcoming of the food)when

3、bell rings againX O X Learned behaviours are adaptive and thus are essential for animals to survive in the changing environment e.g.,they may learn not to eat certain foods if they have ever become ill after eating them more learned behaviours more intelligentIvan Petrovitch Pavlov and William Gantt

4、.“Lectures on conditioned reflexes:Twenty-five years of objective study of the higher nervous activity(behaviour)of animals.”.In:(1928).AI agent as a systemAI agent as a system!Agent(|)Perception:(|,)Actuator:WorldMutual information I(X,O)A systematic viewA systematic view The definition of an AI ag

5、ent depends on the existence of boundaries Closed systems Open systemAgent systemExchange of energyAgent systemExchange of energyExchange of matterThe second law of thermodynamicsThe second law of thermodynamics Closed systems !#=Agent systemExchange of energy!#:freeenergy:energy:temperature:entropy

6、 change!#Bejan,Adrian.Advanced engineering thermodynamics.John Wiley&Sons,2016.Maxwells demonMaxwells demonBy detecting the positions and velocities of gas molecules in two neighbouring chambers and using the information to control the door,the intelligent being could create a temperature difference

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本文探讨了人工智能(AI)代理作为系统的物理基础,强调了学习在生物体适应环境中的作用,并通过Maxwell的恶魔示例说明了AI代理如何减少系统的总熵。文章提出,AI代理需要维持一个世界模型来学习和制定最优策略,同时减少自身熵,以符合第二定律。关键数据包括:AI代理通过学习获得的每比特信息能量最大为kbTln2,其中kb是玻尔兹曼常数,T是温度。Szilard引擎与AI代理的结合展示了在等温条件下,智能反馈控制可以实现熵的减少。结论部分指出,简单的AI代理至少包含感知-决策循环,AI代理系统应被视为一个整体,AI代理能够降低外部世界的熵,但需要能量来维持其世界模型和最优策略。
"AI智能如何降低外部世界熵?" "AI智能行为背后的能量与信息关系是什么?" "如何构建一个具有感知-决策循环的简单AI代理?"
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