Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Universal Artificial Intelligence: Sequential Decisions Based On Algorithmic Probability
Universal Artificial Intelligence: Sequential Decisions Based On Algorithmic Probability
Provably bounded-optimal agents
Journal of Artificial Intelligence Research
Self-modification and mortality in artificial agents
AGI'11 Proceedings of the 4th international conference on Artificial general intelligence
Delusion, survival, and intelligent agents
AGI'11 Proceedings of the 4th international conference on Artificial general intelligence
Information, utility and bounded rationality
AGI'11 Proceedings of the 4th international conference on Artificial general intelligence
Memory issues of intelligent agents
AGI'12 Proceedings of the 5th international conference on Artificial General Intelligence
Memory issues of intelligent agents
AGI'12 Proceedings of the 5th international conference on Artificial General Intelligence
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This paper presents the first formal measure of intelligence for agents fully embedded within their environment. Whereas previous measures such as Legg's universal intelligence measure and Russell's bounded optimality provide theoretical insights into agents that interact with an external world, ours describes an intelligence that is computed by, can be modified by, and is subject to the time and space constraints of the environment with which it interacts. Our measure merges and goes beyond Legg's and Russell's, leading to a new, more realistic definition of artificial intelligence that we call Space-Time Embedded Intelligence.