153 citations · 1.2k across the 73 of their papers we have counts for
4 papers · 1 filter
No Free Lunch versus Occam's Razor in Supervised Learning
Tor Lattimore, Marcus Hutter
The No Free Lunch theorems are often used to argue that domain specific knowledge is required to design successful algorithms. We use algorithmic information theory to argue the ca…
Asymptotically Optimal Agents
Tor Lattimore, Marcus Hutter
Artificial general intelligence aims to create agents capable of learning to solve arbitrary interesting problems. We define two versions of asymptotic optimality and prove that no…
Universal Prediction of Selected Bits
Tor Lattimore, Marcus Hutter, Vaibhav Gavane
Many learning tasks can be viewed as sequence prediction problems. For example, online classification can be converted to sequence prediction with the sequence being pairs of input…
Time Consistent Discounting
Tor Lattimore, Marcus Hutter
A possibly immortal agent tries to maximise its summed discounted rewards over time, where discounting is used to avoid infinite utilities and encourage the agent to value current…