Recording and analysing knowledge-based distributed deduction processes
Journal of Symbolic Computation - Special issue on parallel symbolic computation
WALDMEISTER - High-Performance Equational Deduction
Journal of Automated Reasoning
Distributing Equational Theorem Proving
RTA '93 Proceedings of the 5th International Conference on Rewriting Techniques and Applications
Goal Oriented Equational Theorem Proving Using Team Work
KI '94 Proceedings of the 18th Annual German Conference on Artificial Intelligence: Advances in Artificial Intelligence
Planning for Distributed Theorem Proving: The Teamwork Approach
KI '96 Proceedings of the 20th Annual German Conference on Artificial Intelligence: Advances in Artificial Intelligence
Learning Domain Knowledge to Improve Theorem Proving
CADE-13 Proceedings of the 13th International Conference on Automated Deduction: Automated Deduction
Specification-Based Browsing of Software Component Libraries
Automated Software Engineering
The CADE-14 ATP System Competition
Journal of Automated Reasoning
Combining Parallel and Distributed Search in Automated Equational Deduction
PPAM '01 Proceedings of the th International Conference on Parallel Processing and Applied Mathematics-Revised Papers
E-SETHEO: Design, Configuration and Use of a Parallel Automated Theorem Prover
AI '99 Proceedings of the 12th Australian Joint Conference on Artificial Intelligence: Advanced Topics in Artificial Intelligence
Scheduling Methods for Parallel Automated Theorem Proving
AI '00 Proceedings of the 13th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
CADE-16 Proceedings of the 16th International Conference on Automated Deduction: Automated Deduction
IJCAR '01 Proceedings of the First International Joint Conference on Automated Reasoning
Octopus: Combining Learning and Parallel Search
Journal of Automated Reasoning
The design and implementation of VAMPIRE
AI Communications - CASC
AI Communications - CASC
Filter-based resolution principle for lattice-valued propositional logic LP(X)
Information Sciences: an International Journal
Automated reasoning: past story and new trends
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
ILF and DAWN for Verifying Distributed Algorithms - An Idea for a Tool
Fundamenta Informaticae
First-Order theorem proving and vampire
CAV'13 Proceedings of the 25th international conference on Computer Aided Verification
Simple and efficient clause subsumption with feature vector indexing
Automated Reasoning and Mathematics
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The DISCOUNT system is a distributed equational theorem prover based on the teamwork method for knowledge-based distribution. It uses an extended version of unfailing Knuth–Bendix completion that is able to deal with arbitrarily quantified goals. DISCOUNT features many different control strategies that cooperate using the teamwork approach. Competition between multiple strategies, combined with reactive planning, results in an adaptation of the whole system to given problems, and thus in a very high degree of independence from user interaction. Teamwork also provides a suitable framework for the use of control strategies based on learning from previous proof experiences. One of these strategies forms the core of the expert global_learn, which is capable of learning from successful proofs of several problems. This expert, running sequentially, was one of the entrants in the competition (DISCOUNT/GL), while a distributed DISCOUNT system running on two workstations was another entrant.