Journal of Automated Reasoning
E-SETHEO: An Automated3 Theorem Prover
TABLEAUX '00 Proceedings of the International Conference on Automated Reasoning with Analytic Tableaux and Related Methods
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
MPTP 0.2: Design, Implementation, and Initial Experiments
Journal of Automated Reasoning
The design and implementation of VAMPIRE
AI Communications - CASC
AI Communications - CASC
iProver --- An Instantiation-Based Theorem Prover for First-Order Logic (System Description)
IJCAR '08 Proceedings of the 4th international joint conference on Automated Reasoning
MaLARea SG1 - Machine Learner for Automated Reasoning with Semantic Guidance
IJCAR '08 Proceedings of the 4th international joint conference on Automated Reasoning
SATzilla: portfolio-based algorithm selection for SAT
Journal of Artificial Intelligence Research
The TPTP Problem Library and Associated Infrastructure
Journal of Automated Reasoning
TACAS'08/ETAPS'08 Proceedings of the Theory and practice of software, 14th international conference on Tools and algorithms for the construction and analysis of systems
Extending Sledgehammer with SMT solvers
CADE'11 Proceedings of the 23rd international conference on Automated deduction
Automatic proof and disproof in Isabelle/HOL
FroCoS'11 Proceedings of the 8th international conference on Frontiers of combining systems
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Picking the right search strategy is important for the success of automatic theorem provers. E-MaLeS is a meta-system that uses machine learning and strategy scheduling to optimize the performance of the first-order theorem prover E. E-MaLeS applies a kernel-based learning method to predict the run-time of a strategy on a given problem and dynamically constructs a schedule of multiple promising strategies that are tried in sequence on the problem. This approach has significantly improved the performance of E 1.6, resulting in the second place of E-MaLeS 1.1 in the FOF divisions of CASC-J6 and CASC@Turing.