Universal Knowledge-Seeking Agents for Stochastic Environments
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[1] Jürgen Schmidhuber,et al. Developmental robotics, optimal artificial curiosity, creativity, music, and the fine arts , 2006, Connect. Sci..
[2] Marcus Hutter,et al. Sequential Decisions based on Algorithmic Probability , 2008 .
[3] Ray J. Solomonoff,et al. Complexity-based induction systems: Comparisons and convergence theorems , 1978, IEEE Trans. Inf. Theory.
[4] Marcus Hutter,et al. Universal Artificial Intellegence - Sequential Decisions Based on Algorithmic Probability , 2005, Texts in Theoretical Computer Science. An EATCS Series.
[5] Richard S. Sutton,et al. Reinforcement Learning: An Introduction , 1998, IEEE Trans. Neural Networks.
[6] Marcus Hutter,et al. Universal Artificial Intelligence: Sequential Decisions Based on Algorithmic Probability (Texts in Theoretical Computer Science. An EATCS Series) , 2006 .
[7] Laurent Orseau,et al. Asymptotic non-learnability of universal agents with computable horizon functions , 2013, Theor. Comput. Sci..
[8] Tor Lattimore,et al. Asymptotically Optimal Agents , 2011, ALT.
[9] Pierre-Yves Oudeyer,et al. Active learning of inverse models with intrinsically motivated goal exploration in robots , 2013, Robotics Auton. Syst..
[10] S. Hochreiter,et al. REINFORCEMENT DRIVEN INFORMATION ACQUISITION IN NONDETERMINISTIC ENVIRONMENTS , 1995 .
[11] Tor Lattimore,et al. Time Consistent Discounting , 2011, ALT.
[12] Marcus Hutter,et al. A Philosophical Treatise of Universal Induction , 2011, Entropy.
[13] Yi Sun,et al. Planning to Be Surprised: Optimal Bayesian Exploration in Dynamic Environments , 2011, AGI.
[14] Laurent Orseau,et al. Universal knowledge-seeking agents , 2011, Theor. Comput. Sci..
[15] Ming Li,et al. An Introduction to Kolmogorov Complexity and Its Applications , 2019, Texts in Computer Science.