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Learning Portable Symbolic Representations
2018
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
An open question in artificial intelligence is how to learn useful representations of the real world. One approach is to learn symbols, which represent the world and its contents, as well as models describing the effects on these symbols when interacting with the world. To date, however, research has investigated learning such representations for a single specific task. Our research focuses on approaches to learning these models in a domain-independent manner. We intend to use these symbolic
doi:10.24963/ijcai.2018/826
dblp:conf/ijcai/James18
fatcat:7bme73ud4bhpna5g43dzuqm6q4