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of the AAAI Conference on Artificial Intelligence (Vol. 26, No. 1, pp. 267-273). - Blau, T., Bonilla, E. V., Chades, I., & Dezfouli, A. (2022, June). Optimizing sequential experimental design with deep
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for inference, yet differs from standard Bayesian approaches through its information-theoretic foundation. The MML87 approximation achieves computational tractability while remaining virtually identical to Strict
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approaches. Apply hybrid optimisation techniques (e.g., quantum-inspired or QAOA-based methods) to determine optimal intervention strategies under resource constraints. Compare the performance, scalability
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cooperating with each other, but in many cases competing for individual gains. This structure may not always work for the benefit of science. The purpose of this project is to use game theory and computational
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operators for these notions. Over the past fifty years, such non-classical logics have proved vital in computer science and logic-based artificial intelligence: after all, any intelligent agent must be able
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the Faculty of Science. We will apply Bayesian approaches such as the information-theoretic minimum message length (MML) principle and other approaches to develop a path towards statistically-optimal algorithms