publication . Preprint . 2017

Minimally Naturalistic Artificial Intelligence

Hansen, Steven Stenberg;
Open Access English
  • Published: 13 Jan 2017
Abstract
Comment: Accepted into the NIPS 2016 Workshop on Machine Intelligence (M.A.I.N.)
Subjects
free text keywords: Computer Science - Artificial Intelligence
Related Organizations
Download from

[1] Wolpert, D. H., & Macready, W. G. (1997). No free lunch theorems for optimization. IEEE transactions on evolutionary computation, 1(1), 67-82. [OpenAIRE]

[2] Minsky, M. L., Singh, P., & Sloman, A. (2004). The St. Thomas common sense symposium: designing architectures for human-level intelligence. AI Magazine, 25(2), 113.

[3] Mikolov, T., Joulin, A., & Baroni, M. (2015). A roadmap towards machine intelligence. arXiv preprint arXiv:1511.08130. [OpenAIRE]

[4] Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A. A., Veness, J., Bellemare, M. G., ... & Petersen, S. (2015). Human-level control through deep reinforcement learning. Nature, 518(7540), 529-533. [OpenAIRE]

[5] Loftin, R., Peng, B., MacGlashan, J., Littman, M. L., Taylor, M. E., Huang, J., & Roberts, D. L. (2016). Learning behaviors via human-delivered discrete feedback: modeling implicit feedback strategies to speed up learning. Autonomous Agents and Multi-Agent Systems, 30(1), 30-59.

[6] Ullman, T., Baker, C., Macindoe, O., Evans, O., Goodman, N., & Tenenbaum, J. B. (2009). Help or hinder: Bayesian models of social goal inference. In Advances in neural information processing systems (pp. 1874-1882).

[7] Branavan, S. R. K., Silver, D., & Barzilay, R. (2011, June). Learning to win by reading manuals in a MonteCarlo framework. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies-Volume 1 (pp. 268-277). Association for Computational Linguistics. [OpenAIRE]

Powered by OpenAIRE Research Graph
Any information missing or wrong?Report an Issue