8 research outputs found
An efficient contradiction separation based automated deduction algorithm for enhancing reasoning capability
Automated theorem prover (ATP) for first-order logic (FOL), as a significant inference engine, is one of the hot research areas in the field of knowledge representation and automated reasoning. E prover, as one of the leading ATPs, has made a significant contribution to the development of theorem provers for FOL, particularly equality handling, after more than two decades of development. However, there are still a large number of problems in the TPTP problem library, the benchmark problem library for ATPs, that E has yet to solve. The standard contradiction separation (S-CS) rule is an inference method introduced recently that can handle multiple clauses in a synergized way and has a few distinctive features which complements to the calculus of E. Binary clauses, on the other hand, are widely utilized in the automated deduction process for FOL because they have a minimal number of literals (typically only two literals), few symbols, and high manipulability. As a result, it is feasible to improve a prover's deduction capability by reusing binary clause. In this paper, a binary clause reusing algorithm based on the S-CS rule is firstly proposed, which is then incorporated into E with the objective to enhance E’s performance, resulting in an extended E prover. According to experimental findings, the performance of the extended E prover not only outperforms E itself in a variety of aspects, but also solves 18 problems with rating of 1 in the TPTP library, meaning that none of the existing ATPs are able to resolve them
GRUNGE: A Grand Unified ATP Challenge
This paper describes a large set of related theorem proving problems obtained
by translating theorems from the HOL4 standard library into multiple logical
formalisms. The formalisms are in higher-order logic (with and without type
variables) and first-order logic (possibly with multiple types, and possibly
with type variables). The resultant problem sets allow us to run automated
theorem provers that support different logical formats on corresponding
problems, and compare their performances. This also results in a new "grand
unified" large theory benchmark that emulates the ITP/ATP hammer setting, where
systems and metasystems can use multiple ATP formalisms in complementary ways,
and jointly learn from the accumulated knowledge.Comment: CADE 27 -- 27th International Conference on Automated Deductio
Knowledge and Management Models for Sustainable Growth
In the last years sustainability has become a topic of global concern and a key issue in the strategic agenda of both business organizations and public authorities and organisations.
Significant changes in business landscape, the emergence of new technology, including social media, the pressure of new social concerns, have called into question established conceptualizations of competitiveness, wealth creation and growth.
New and unaddressed set of issues regarding how private and public organisations manage and invest their resources to create sustainable value have brought to light. In particular the increasing focus on environmental and social themes has suggested new dimensions to be taken into account in the value creation dynamics, both at organisations and communities level.
For companies the need of integrating corporate social and environmental responsibility issues into strategy and daily business operations, pose profound challenges, which, in turn, involve numerous processes and complex decisions influenced by many stakeholders. Facing these challenges calls for the creation, use and exploitation of new knowledge as well as the development of proper management models, approaches and tools aimed to contribute to the development and realization of environmentally and socially sustainable business strategies and practices
Assuming Data Integrity and Empirical Evidence to The Contrary
Background: Not all respondents to surveys apply their minds or understand
the posed questions, and as such provide answers which lack coherence, and
this threatens the integrity of the research. Casual inspection and limited
research of the 10-item Big Five Inventory (BFI-10), included in the dataset of
the World Values Survey (WVS), suggested that random responses may be
common.
Objective: To specify the percentage of cases in the BRI-10 which include
incoherent or contradictory responses and to test the extent to which the
removal of these cases will improve the quality of the dataset.
Method: The WVS data on the BFI-10, measuring the Big Five Personality (B5P), in South Africa (N=3 531), was used. Incoherent or contradictory responses were removed. Then the cases from the cleaned-up dataset were analysed for their theoretical validity.
Results: Only 1 612 (45.7%) cases were identified as not including incoherent
or contradictory responses. The cleaned-up data did not mirror the B5P- structure, as was envisaged. The test for common method bias was negative. Conclusion: In most cases the responses were incoherent. Cleaning up the data did not improve the psychometric properties of the BFI-10. This raises concerns about the quality of the WVS data, the BFI-10, and the universality of B5P-theory. Given these results, it would be unwise to use the BFI-10 in South Africa. Researchers are alerted to do a proper assessment of the
psychometric properties of instruments before they use it, particularly in a
cross-cultural setting