Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence

The IJCAI-09 Workshop on Learning Structural Knowledge From Observations (STRUCK-09) took place as part of the International Joint Conference on Artificial Intelligence (IJCAI-09) on July 12 in Pasadena, California. The workshop program included paper presentations, discussion sessions about those papers, group discussions about two selected topic and a joint discussion.

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Federated Reinforcement Distillation with Proxy Experience Memory

10.36227/techrxiv.12645497 ◽

2020 ◽

Author(s):

Han Cha ◽

Jihong Park ◽

Hyesung Kim ◽

Seong-Lyun Kim ◽

Mehdi Bennis

Keyword(s):

Artificial Intelligence ◽

Machine Learning ◽

Data Confidentiality ◽

User Privacy ◽

Joint Conference ◽

International Joint

This paper is presented at 28th International Joint Conference on Artificial Intelligence (IJCAI-19) 1st Wksp. Federated Machine Learning for User Privacy and Data Confidentiality (FML'19), Macau, August 2019.

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Proof Complexity of Modal Resolution

Journal of Automated Reasoning ◽

10.1007/s10817-021-09609-9 ◽

2021 ◽

Author(s):

Sarah Sigley ◽

Olaf Beyersdorff

Keyword(s):

Artificial Intelligence ◽

Automated Reasoning ◽

Proof Complexity ◽

Pigeonhole Principle ◽

Analytic Tableaux ◽

Frege Systems ◽

International Joint ◽

Resolution Proofs ◽

Exponential Size ◽

Sixth International

AbstractWe investigate the proof complexity of modal resolution systems developed by Nalon and Dixon (J Algorithms 62(3–4):117–134, 2007) and Nalon et al. (in: Automated reasoning with analytic Tableaux and related methods—24th international conference, (TABLEAUX’15), pp 185–200, 2015), which form the basis of modal theorem proving (Nalon et al., in: Proceedings of the twenty-sixth international joint conference on artificial intelligence (IJCAI’17), pp 4919–4923, 2017). We complement these calculi by a new tighter variant and show that proofs can be efficiently translated between all these variants, meaning that the calculi are equivalent from a proof complexity perspective. We then develop the first lower bound technique for modal resolution using Prover–Delayer games, which can be used to establish “genuine” modal lower bounds for size of dag-like modal resolution proofs. We illustrate the technique by devising a new modal pigeonhole principle, which we demonstrate to require exponential-size proofs in modal resolution. Finally, we compare modal resolution to the modal Frege systems of Hrubeš (Ann Pure Appl Log 157(2–3):194–205, 2009) and obtain a “genuinely” modal separation.

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