scholarly journals Bayesian Optimisation for Heuristic Configuration in Automated Theorem Proving

10.29007/q91g ◽  
2020 ◽  
Author(s):  
Agnieszka Słowik ◽  
Chaitanya Mangla ◽  
Mateja Jamnik ◽  
Sean Holden ◽  
Lawrence Paulson
Keyword(s):  
Theorem Proving ◽  
Automated Theorem Proving ◽  
Probabilistic Framework ◽  
Selection Algorithm ◽  
Formal Proofs ◽  
Proof Search ◽  
Minimum Number ◽  
Selection Algorithms

Modern theorem provers such as Vampire utilise premise selection algorithms to control the proof search explosion. Premise selection heuristics often employ an array of continuous and discrete parameters. The quality of recommended premises varies depending on the parameter assignment. In this work, we introduce a principled probabilistic framework for optimisation of a premise selection algorithm. We present results using Sumo Inference Engine (SInE) and the Archive of Formal Proofs (AFP) as a case study. Our approach can be used to optimise heuristics on large theories in minimum number of steps.

scholarly journals Bayesian Optimisation for Premise Selection in Automated Theorem Proving (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13919-13920
Author(s):  
Agnieszka Słowik ◽  
Chaitanya Mangla ◽  
Mateja Jamnik ◽  
Sean B. Holden ◽  
Lawrence C. Paulson
Keyword(s):  
Parameter Space ◽  
Theorem Proving ◽  
Automated Theorem Proving ◽  
Search Space ◽  
Large Set ◽  
Probabilistic Framework ◽  
Formal Proofs ◽  
Dimensional Parameter ◽  
Theorem Provers

Modern theorem provers utilise a wide array of heuristics to control the search space explosion, thereby requiring optimisation of a large set of parameters. An exhaustive search in this multi-dimensional parameter space is intractable in most cases, yet the performance of the provers is highly dependent on the parameter assignment. In this work, we introduce a principled probabilistic framework for heuristic optimisation in theorem provers. We present results using a heuristic for premise selection and the Archive of Formal Proofs (AFP) as a case study.

WS-SIM: A Toolkit for Modeling and Simulation of Service Composition

2013 ◽  
Vol 756-759 ◽  
pp. 1304-1308
Author(s):  
Fan Zhang
Keyword(s):  
Web Service ◽  
Service Composition ◽  
Simulation Experiment ◽  
Service Selection ◽  
Selection Algorithm ◽  
Web Service Selection ◽  
Composite Services ◽  
Selection Algorithms

Web service has been rapidly developed in recent years. Web service selection is an important issue in web service composition and lots of service selection algorithms have been presented. As lots of them select an atomic service during runtime, it is not an easy task to evaluate the quality of the composited service which composed of several atomic services. In this work we introduce WS-SIM, a simulation toolkit, to solve this problem. WS-SIM supports modeling and simulating composite services and atomic services in the real world. This system also provides many common service selection algorithms and researchers can custom their own service selection algorithm for a simulation experiment. The quality of composite services can also be generated by our system. Furthermore, to demonstrate suitability of the WS-SIM, in this paper, functionalities of our system are illustrated by a case study. This confirms the usability and the applicability of WS-SIM.

A Network Selection Algorithm with Parallel Transmission Based on MADM

2014 ◽  
Vol 556-562 ◽  
pp. 4606-4611 ◽  
Author(s):  
Li Na Zhang ◽  
Qi Zhu
Keyword(s):  
Wireless Networks ◽  
Quality Of Service ◽  
Heterogeneous Wireless Networks ◽  
Network Selection ◽  
Selection Algorithm ◽  
Decision Matrix ◽  
Parallel Transmission ◽  
User Throughput ◽  
Selection Algorithms

At present, most of researches on network selection algorithms are focused on single access. To support seamless mobility and provide better quality of service in heterogeneous wireless networks, this paper proposes a network selection algorithm with parallel transmission based on MADM. In the algorithm, we firstly determine all available wireless networks and consider every subset of these networks as a network scheme. Then we obtain aggregation attributes of every scheme and determine the alternative network schemes. Finally, we build the decision matrix of multiple attributes and determine the optimal scheme by using GRA. Simulation results show that the proposed algorithm can obviously improve user quality of service, improve user throughput, reduce power consumption and price cost per bit.

scholarly journals V.M. Glushkov and automated theorem proving in Ukraine: evidence algorithm evidence algorithm and SAD systems

2020 ◽  
Vol 4 ◽  
pp. 3-10
Author(s):  
O.V. Lyaletski ◽  
Keyword(s):  
Theorem Proving ◽  
Automated Theorem Proving ◽  
English Language ◽  
Mathematical Reasoning ◽  
Russian Language ◽  
Automated Deduction ◽  
Current Time ◽  
Proof Search ◽  
Online Mode ◽  
Evidence Algorithm

Fifty years ago, in 1970, Academician V.M. Glushkov published a paper, in which he, along with a discussion of some problems of artificial intelligence, formulated a research program called Evidence Algorithm (EA) describing his vision of the problem of a computer support of human activity in looking for a proof of a particular theorem. V.M. Glushkov proposed to focus attention on the construction of an automated theorem-proving system performing simultaneous investigations in: creating formal natural languages for writing mathematical texts in a form accustomed to a human, constructing a procedure for a proof search based on the evolutionary developing of the machine notion of an evidence of a computer-made proof step, using the knowledge gained by the system during its operation and providing a user with the opportunity to assist to the system in its proof search process. Since the inception of EA, two serious attempts have been made to implement this program. The first led to the emergence in 1978 of a Russian-language automated theorem proving and the second led to the appearance in 2002 of its English-language modification named System for Automated Deduction (SAD). And if the development and trial operation of the first system were discontinued in 1992 after the output from service of the ES-line computers, on which it was realized, the SAD system, being placed on the website “nevidal.org”, is now still available in online mode. That is, at the current time, it is possible to carry out different experiments with the SAD system and to solve various problems that require rigorous mathematical reasoning. This work is devoted to a chronological description of studies on the implementation of the EA program for the entire period of its existence and to the highlighting of peculiarities of both the systems, as well as of their common features and distinguishes. Some possible ways of the further development of the SAD system are given.

scholarly journals We know (nearly) nothing!l But can we learn?

10.29007/n7rd ◽  
2018 ◽  
Author(s):  
Stephan Schulz
Keyword(s):  
Theorem Proving ◽  
Automated Theorem Proving ◽  
Homogeneous Problem ◽  
Empirical Evaluation ◽  
Optimization Techniques ◽  
Proof Search ◽  
Search Heuristics ◽  
Order Of Magnitude ◽  
Automated Optimization

The greatest source of progress in automated theorem proving in the last 30 years has been the development of better search heuristics, usually based on developer experience and empirical evaluation, but increasingly also using automated optimization techniques. Despite this progress, we still know very little about proof search. We have mostly failed to identify good features for characterizing homogeneous problem classes, or for identifying interesting and relevant clauses and formulas.I propose the challenge of bringing together inductive techniques (generalization and learning) and deductive techniques to attack this problem. Hardware and software have finally evolved to a point that we can reasonably represent and analyze large proof searches and search decisions, and where we can hope to achieve order-of-magnitude improvements in the efficiency of the proof search.

scholarly journals Different Proofs are Good Proofs

10.29007/kwk9 ◽  
2018 ◽  
Author(s):  
Geoff Sutcliffe ◽  
Cynthia Chang ◽  
Li Ding ◽  
Deborah McGuinness ◽  
Paulo Pinheiro da Silva
Keyword(s):  
Theorem Proving ◽  
Automated Theorem Proving ◽  
Order Logic ◽  
First Order Logic ◽  
First Order ◽  
Problem Library

In order to compare the quality of proofs, it is necessary to measure artifacts of the proofs, and evaluate the measurements to determine differences between the proofs. This paper discounts the approach of ranking measurements of proof artifacts, and takes the position that different proofs are good proofs. The position is based on proofs in the TSTP solution library, which are generated by Automated Theorem Proving (ATP) systems applied to first-order logic problems in the TPTP problem library.

scholarly journals Checking the quality of clinical guidelines using automated reasoning tools

2008 ◽  
Vol 8 (5-6) ◽  
pp. 611-641 ◽  
Author(s):  
ARJEN HOMMERSOM ◽  
PETER J. F. LUCAS ◽  
PATRICK VAN BOMMEL
Keyword(s):  
Theorem Proving ◽  
Clinical Guidelines ◽  
Automated Reasoning ◽  
Automated Theorem Proving ◽  
Interactive Theorem Proving ◽  
Theorem Prover ◽  
First Order ◽  
Medical Quality ◽  
Diabetes Mellitus 2

AbstractRequirements about the quality of clinical guidelines can be represented by schemata borrowed from the theory of abductive diagnosis, using temporal logic to model the time-oriented aspects expressed in a guideline. Previously, we have shown that these requirements can be verified using interactive theorem proving techniques. In this paper, we investigate how this approach can be mapped to the facilities of a resolution-based theorem prover,otterand a complementary program that searches for finite models of first-order statements,mace-2. It is shown that the reasoning required for checking the quality of a guideline can be mapped to such a fully automated theorem-proving facilities. The medical quality of an actual guideline concerning diabetes mellitus 2 is investigated in this way.

Sign in / Sign up

Export Citation Format

Share Document