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In this report, we introduce an artificial dataset generator for Photo-realistic Blocksworld domain.
Procedures as a Representation for Data in a Computer Program for Understanding Natural Language
Winograd, T. (1971) · 1971
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Sussman, G. J. (1973)
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The Nonlinear Nature of Plans
Sacerdoti, E. D. (1975) · 1975
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Achieving Several Goals Simultaneously
Waldinger, R. (1975) · 1975
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Introduction to Artificial Intelligence
McDermott, D., & Charniak, E. (1985) · 1985
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On the Complexity of Blocks-World Planning
Gupta, N., & Nau, D. S. (1992) · 1992
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Paradigms of Artificial Intelligence Programming: Case Studies in Common LISP
Norvig, P. (1992) · 1992
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Complexity Results for SAS+ Planning
Bäckström, C., & Nebel, B. (1995) · 1995
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The 1998 AI Planning Systems Competition
McDermott, D. V. (2000) · 1998
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Blocks World Revisited
Slaney, J., & Thiébaux, S. (2001) · 2001
Cited alongside, same era.
A Planning Heuristic Based on Causal Graph Analysis
Helmert, M. (2004) · 2004
Cited alongside, same era.
Joint Activity Testbed: Blocks World for Teams (BW4T)
Johnson, M., Jonker, C., Van Riemsdijk, B., Feltovich, P. J., & Bradshaw, J. M. (2009) · 2009
Cited alongside, same era.
The Arcade Learning Environment: An Evaluation Platform for General Agents
Bellemare, M. G., Naddaf, Y., Veness, J., & Bowling, M. (2013) · 2013
Cited alongside, same era.
Towards a Dataset for Human Computer Communication via Grounded Language Acquisition.
Bisk, Y., Marcu, D., & Wong, W. (2016) · 2016
Later among the works it cites.
You Only Look Once: Unified, Real-Time Object Detection
Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016) · 2016
Later among the works it cites.
Learning interpretable spatial operations in a rich 3d blocks world
Bisk, Y., Shih, K. J., Choi, Y., & Marcu, D. (2017) · 2017
Later among the works it cites.
CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning
Johnson, J., Hariharan, B., van der Maaten, L., Fei-Fei, L., Zitnick, C. L., & Girshick, R. (2017) · 2017
Later among the works it cites.
Classical Planning in Deep Latent Space: Bridging the Subsymbolic-Symbolic Boundary
Asai, M., & Fukunaga, A. (2018) · 2018
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Back to the blocks world: Learning new actions through situated human-robot dialogue
She, L., Yang, S., Cheng, Y., Jia, Y., Chai, J., & Xi, N. (2014) · 2014
Cited alongside, same era.
LSTM-Based Goal Recognition in Latent Space
Amado, L., Aires, J. P., Pereira, R. F., Magnaguagno, M. C., Granada, R., & Meneguzzi, F. (2018a)
Cited in the paper.
Goal Recognition in Latent Space.
Amado, L., Pereira, R. F., Aires, J., Magnaguagno, M., Granada, R., & Meneguzzi, F. (2018b)
Cited in the paper.
Learning Plannable Representations with Causal InfoGAN
Kurutach, T., Tamar, A., Yang, G., Russell, S., & Abbeel, P. (2018) · 2018
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Building and learning structures in a situated blocks world through deep language understanding
Perera, I., Allen, J., Teng, C. M., & Galescu, L. (2018) · 2018
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