## Hidden Markov Models: useful for speech etc. But discrete, cannot store real values, no good algorithms for learning appropriate topologies

## Symbolic approaches: useful for grammar learning. Not for real-valued noisy sequences.

## Heuristic program search (e.g., Genetic Programming, Cramer 1985): no direction for search in algorithm space.

## Universal Search (Levin 1973): asymptotically optimal, but huge constant slowdown factor

## Fastest algorithm for all well-defined problems (Hutter, 2001): asymptotically optimal, but huge additive constant.

## Optimal ordered problem solver (Schmidhuber, 2002)

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