Neural networks with relational memory

A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to implement:

• a memory configured to store a respective memory vector at each of a plurality of memory locations in the memory;
• and
• a memory-based neural network, wherein the memory-based neural network is configured to:
• at each of a plurality of time steps:
• receive an input;
• determine an update to the memory, wherein determining the update comprises applying an attention mechanism over (i) the memory vectors in the memory and (ii) memory vectors in an appended memory that is generated by appending the received input to the memory, wherein applying the attention mechanism over the memory vectors in the memory and memory vectors in the appended memory comprises:
• generating, from a subset of the memory vectors in the memory, a query matrix,
• generating, from a subset of the memory vectors in the appended memory, a key matrix,
• generating, from the subset of the memory vectors in the appended memory, a value matrix,
• generating, from (i) the query matrix generated from the subset of the memory vectors in the memory and (ii) the key matrix generated from the subset of the memory vectors in the appended memory, a weight matrix, and
• determining a first update to the memory based on the weight matrix and the value matrix generated from the subset of the memory vectors in the appended memory;
• update the memory using the determined update to the memory;
• and
• generate an output for the current time step using the updated memory.