Predicting t+1 from a set of sequences
Say I have have an experiment where I release a single rat into a maze and wait for it to reach the end. Say I also track this rat's position in the maze at various times. Let's do this $n$ times. Now, I have a dataset of $n$ variable-length movement profiles, since some of the animals finish faster, some take longer, etc. Is there a way I can analyze this data to then predict the next move $(x_{t+1}, y_{t+1})$ given an $(x_t, y_t)$? What techniques could I use and how would they work? I was thinking LSTM or RNNs, but unsure what techniques are used for problems like this.
Topic lstm rnn neural-network predictive-modeling
Category Data Science