2024
Bibliographic References tagged with 2024
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T. Werner, I. Soraperra, E. Calvano, D. C. Parkes, and I. Rahwan,
“Experimental evidence that conversational artificial intelligence can steer consumer behavior without detection”, arXiv preprint arXiv:2409, 2024.
T. Werner, I. Soraperra, E. Calvano, D. C. Parkes, and I. Rahwan,
“Experimental evidence that conversational artificial intelligence can steer consumer behavior without detection”, arXiv preprint arXiv:2409, 2024.
H. Zhang and D. C. Parkes,
“Chain-of-thought reasoning is a policy improvement operator”, arXiv preprint arXiv:2309.08589, 2024.
H. Zhang and D. C. Parkes,
“Chain-of-thought reasoning is a policy improvement operator”, arXiv preprint arXiv:2309.08589, 2024.
S. S. Ravindranath, Z. Feng, D. Wang, M. Zaheer, A. Mehta, and D. C. Parkes,
“Deep reinforcement learning for sequential combinatorial auctions”, arXiv preprint arXiv:2407.08022, 2024.
S. S. Ravindranath, Z. Feng, D. Wang, M. Zaheer, A. Mehta, and D. C. Parkes,
“Deep reinforcement learning for sequential combinatorial auctions”, arXiv preprint arXiv:2407.08022, 2024.
M. Wuthrich, M. York, and D. C. Parkes,
M. Wuthrich, M. York, and D. C. Parkes,
S. Hossain, T. Wang, T. Lin, Y. Chen, D. Parkes, and H. Xu,
S. Hossain, T. Wang, T. Lin, Y. Chen, D. Parkes, and H. Xu,
T. Wang, Y. Jiang, and D. Parkes,
T. Wang, Y. Jiang, and D. Parkes,
M. H. Tessler et al.,
“AI can help humans find common ground in democratic deliberation”, Science, vol. 386, no. 6719, 2024.
M. H. Tessler et al.,
“AI can help humans find common ground in democratic deliberation”, Science, vol. 386, no. 6719, 2024.
E. Zhang et al.,
“Position: Social Environment Design Should be Further Developed for AI-based Policy-Making”, in Proc. 41st International Conference on Machine Learning, ICML 2024, 2024.
E. Zhang et al.,
“Position: Social Environment Design Should be Further Developed for AI-based Policy-Making”, in Proc. 41st International Conference on Machine Learning, ICML 2024, 2024.
L. D’Amico-Wong, Y. A. Gonczarowski, G. Q. Ma, and D. C. Parkes,
“Disrupting Bipartite Trading Networks: Matching for Revenue Maximization.”, in Proc. Twenty-Fifth ACM Conference on Economics and Computation (EC’24)., 2024.
L. D’Amico-Wong, Y. A. Gonczarowski, G. Q. Ma, and D. C. Parkes,
“Disrupting Bipartite Trading Networks: Matching for Revenue Maximization.”, in Proc. Twenty-Fifth ACM Conference on Economics and Computation (EC’24)., 2024.
P. Duetting, Z. Feng, H. Narasimhan, D. C. Parkes, and S. S. Ravindranath,
“Optimal Auctions through Deep Learning: Advances in Differentiable Economics. ”, J. ACM , vol. 71, no. (1), pp. 5:1–5:53, 2024.
P. Duetting, Z. Feng, H. Narasimhan, D. C. Parkes, and S. S. Ravindranath,
“Optimal Auctions through Deep Learning: Advances in Differentiable Economics. ”, J. ACM , vol. 71, no. (1), pp. 5:1–5:53, 2024.