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Inconsistency robustness is information system performance in the face of continually pervasive inconsistencies---a shift from the previously dominant paradigms of inconsistency denial and inconsistency elimination attempting to sweep them under the rug. Inconsistency robustness is a both an observed phenomenon and a desired feature: • Inconsistency Robustness is an observed phenomenon because large information-systems are required to operate in an environment of pervasive inconsistency. • Inconsistency Robustness is a desired feature because we need to improve the performance of large information system. This volume has revised versions of refereed articles and panel summaries from the first two International Symposia on Inconsistency Robustness conducted under the auspices of the International Society for Inconsistency Robustness (iRobust http://irobust.org). The articles are broadly based on theory and practice, addressing fundamental issues in inconsistency robustness. The field of Inconsistency Robustness aims to provide practical rigorous foundations for computer information systems dealing with pervasively inconsistent information.
- Sales Rank: #1012914 in Books
- Published on: 2015-05-20
- Original language: English
- Number of items: 1
- Dimensions: 9.21" h x 1.24" w x 6.14" l, 1.87 pounds
- Binding: Paperback
- 614 pages
From the Author
Inconsistency robust logic is an important conceptual advance in that requires that nothing "extra" can be inferred just from the presence ofa contradiction. A natural question that arises is the relationship between paraconsistency and inconsistency robustness. It turns out that a paraconsistent logic can allow erroneous inferences from an inconsistency that are not allowed by inconsistency robustness. Of course, an inconsistency robust logic is also necessarily paraconsistent. The goal of Classical Direct Logic (a special case of Inconsistency Robust Direct Logic) is to provide mathematical foundations for Computer Science. Because Direct Logic is strongly typed, it defies Gödel's meta-mathematical results on which is the proposition of the Dedekind/Peano theory of numbers that is true but unprovable.Gödel proposed the sentence "I an not provable." as the true but unprovable sentence. However, Wittgenstein correctly pointed out that Gödel's sentence leads to inconsistency in mathematics. The resolution is that using strong types, it can be shown that Gödel's sentence is not a sentence of mathematics. Consequently Gödel's argument (using his sentence) is incorrect that mathematics cannot prove its own consistency without itself falling into inconsistency. In fact, mathematics formally proves its own consistency (using a very simple proof by contradiction) without evident self-contradiction in mathematics (e.g., all the usual paradoxes such as Russell, Berry, Girad, etc. do not produce inconsistencies).
Operational aspects of Inconsistency Robustness are addressed using the Actor Model of computation and inferential aspects using Direct Logic™. Professor Hewitt is the creator (together with his students and other colleagues) of the Actor Model of computation, which influenced the development of the Scheme programming language and the π calculus, and inspired several other systems and programming languages. The Actor Model is in widespread industrial use including eBay, Microsoft, and Twitter.ActorScript™ and the Actor Model on which it is based can play an important role in the implementation of more inconsistency-robust information systems.
About the Author
Professor Carl Hewitt is the creator (together with his students and other colleagues) of the Actor Model of computation, which influenced the development of the Scheme programming language and the π calculus, and inspired several other systems and programming languages. The Actor Model is in widespread industrial use including eBay, Microsoft, and Twitter. For his doctoral thesis, he designed Planner,the first programming language based on pattern-invoked procedural plans.
Professor Hewitt's recent research centers on the area of Inconsistency Robustness, i.e., system performance in the face of continual,pervasive inconsistencies (a shift from the previously dominant paradigms of inconsistency denial and inconsistency elimination, i.e., to sweeping consistencies under the rug). ActorScript and the Actor Model on which it is based can play an important role in the implementation of more inconsistency-robust information systems.
Hewitt is Board Chair of iRobust™, an international scientific society for the promotion of the field of Inconsistency Robustness. He is also Board Chair of Standard IoT™, an international standards organization for the Internet of Things, which is using the Actor Model to unify and generalize emerging standards for IoT. He has been a Visiting Professor at Stanford University and Keio University and is Emeritus in the EECS department at MIT.
Most helpful customer reviews
3 of 3 people found the following review helpful.
This book is a collection of papers presented at two symposia on the topic
By Fanya S. Montalvo
This book consists of 14 peer-reviewed papers presented at two
Stanford Symposia on this topic in 2011 and 2014. The list of papers
presented are:
5 by Carl Hewitt
"Formalizing common sense reasoning for scalable inconsistency-robust
information integration using Direct Logic Reasoning and the Actor
Model", "Inconsistency robustness in foundations: Mathematics self
proves its own consistency and other matters"," Actor Model of
computation: Scalable robust information systems", "Inconsistency
robustness for logic programs", and "ActorScript extension of C#,
Java, Objective C, JavaScript, and SystemVerilog using iAdaptive
concurrency for antiCloud privacy and security."
John Woods "Inconsistency: Its present impacts and future prospects."
Eric Kao "Two sources of explosion."
Anne Gardner "Some types of inconsistency in legal reasoning."
Stefania Fusco and David Olson "Rules versus standards: Competing
notions of inconsistency: Robustness in the Supreme Court and Federal
Circuit."
Mike Travers "Politics and pragmatism in scientific ontology
construction."
Dan Flickinger "Modelling ungrammaticality in a precise grammar of
English."
Fanya S. Montalvo "The singularity is here."
Catherine Blake "Biological responses to chemical exposure: Case
studies in how to manage ostensible inconsistencies using the Claim
Framework."
Alaa Abi Haidar, Mihnea Tufi, and Jean-Gabriel Ganascia "From
inter-annotation to intra-publication inconsistency."
Since one of these papers is mine, I'm being modest by giving it four stars.
0 of 0 people found the following review helpful.
” The approach defies Gödel’s famous 2nd incompleteness theorem (traditionally deemed to be one of the greatest achievements in
By JJ
Review of: Inconsistency Robustness (Carl Hewitt and John Woods assisted by Jane Spurr, eds.), College Publications, UK. 2015.
by
John-Jules Meyer, Utrecht University, Dept. of Information and Computing Sciences, and Alan Turing Institute Almere, The Netherlands
This is an extraordinary book originating from two extraordinary conferences about a novel way of looking upon logical inconsistencies, Inconsistency Robustness 2011 and 2014, both held at Stanford University in California, USA, in the summers of 2011 and 2014. Instead of trying to avoid them (since in classical logic the whole thing explodes if there is an inconsistency, via the ex falso quodlibet rule), we are led to accept them (since in practice they appear everywhere), and reason with them in a non-classical way.
Inconsistency robust logic is an important conceptual advance in that requires that nothing “extra” can be inferred just from the presence of a contradiction. For example, suppose that there is a language with just two propositions, namely, P and Q. Furthermore, suppose that P and (not P ) are axioms. Then, the only propositions that can be inferred in an inconsistency robust logic are
(P and (not P )), ((not P ) and (not P )), etc. In particular, (P or Q ) cannot be inferred because otherwise Q could be erroneously inferred using (not P ) by the rule of Disjunctive Syllogism. An example of a logic (called NanoIntuitionistic) which is not inconsistency robust has just one rule of inference, namely, classical proof by contradiction. NanoIntuitionistic is not inconsistency robust because (not Q ), (not (not Q )), (not (not P )), etc. can be erroneously inferred from the contradictory axioms P and (not P ). Note that Q cannot be inferred in NanoIntuitionistic (because there is no rule of double negation elimination). Consequently, NanoIntuitionistic is a paraconsistent logic (which was conceived by Stanisław Jaśkowski [Jaśkowski 1948] and then developed by many logicians to deal with inconsistencies in mathematical logic [Arruda 1989; Priest, and Routley 1989]) where a logic is by definition paraconsistent if and only if it is not the case that every proposition can be inferred from an inconsistency. In conclusion, a paraconsistent logic (e.g. NanoIntuitionistic) can allow erroneous inferences (e.g. (not Q )) from an inconsistency that are not allowed by inconsistency robustness. Of course, an inconsistency robust logic is also necessarily paraconsistent.
Previous approaches try to keep inconsistency as minimal as possible, while Hewitt’s approach ‘embraces’ inconsistency as something that cannot be avoided and consequently must be dealt with. Hewitt’s logic, called Direct Logic, has two variants: Classical Direct Logic (for classical mathematical theories thought to be consistent) and Inconsistency Robust Direct Logic (for possibly inconsistent theories) where the main difference is that the former has an ex falso quodlibet principle while the latter has not. Classical Direct Logic is used for the special case of mathematical theories known with high confidence to be consistent, e.g., plane geometry. Both variants of Direct Logic impose that propositions must be typed with the consequence that no (unlimited) “self-referential” sentences can be constructed such as the one used by Gödel to prove his incompleteness theorems. Direct Logic is based on argumentation, which may be viewed as a more computational approach than classical first-order logic.
As Hewitt says in his preface: “The field of Inconsistency Robustness aims to provide practical, rigorous foundations for computer information systems having pervasively inconsistent information in a variety of fields e.g., computer science and engineering, health, management, law, etc.”
The approach defies Gödel’s famous 2nd incompleteness theorem (traditionally deemed to be one of the greatest achievements in logic in the last century),
which states that mathematics, if consistent, cannot prove its own consistency.
In the Classical Direct Logic, mathematics is provably formally consistent! By formally consistent, it is meant that an inconsistency is not inferred. The proof is remarkably tiny consisting of only using proof by contradiction and soundness. In fact, it is so easy that one wonders why this was overlooked by so many great logicians in the past. The proof is also remarkable that it does not use knowledge about the content of mathematical theories (plane geometry, integers, etc.). The proof serves to formalize that consistency is built into the very architecture of classical mathematics. However, the proof of formal consistency does not prove constructive consistency, which is defined to be that the rules of Classical Direct Logic themselves do not derive a contradiction. Proof of constructive consistency requires a separate inductive proof using the axioms and rules of inference of Classical Direct Logic. The upshot is that, contra Gödel, there seems to be no inherent reason that mathematics cannot prove constructive consistency of Classical Direct Logic (which formalizes classical mathematical theories). However, such a proof is far beyond the current state of the art.
The book contains 14 chapters, organised into 3 parts: Mathematical Foundations, Software Foundations and Applications, an index and has 535 pages. The applications part contains chapters on inconsistency in legal reasoning, scientific ontology construction, linguistics, biology and chemistry, and the technological singularity. It contains an extensive preface by Carl Hewitt, in which the very idea of Inconsistency Robustness is motivated and explained intuitively, as well all papers are introduced and put into context.
I briefly go through the chapters. The first two chapters by Hewitt provide the foundations of DL with a focus on the foundations of mathematics and semantics. John Woods presents a well-wrought philosophical-historical perspective to Inconsistency Robustness, in which he BTW concludes that Direct Logic (in both variants) is still very much (admittedly very interesting) work in progress. Eric Kao discusses in a short article the role of principles like the law of excluded middle and proof by self-refutation in the ‘explosive’ character of IRDL. Part 2 deals with software foundations. In three articles Hewitt discusses the Actor Model of concurrent computation, the relation of DL with logic programming and ActorScript. At first sight there might seem to be no direct relation with inconsistency robustness. However, Actors are fundamental to the implementation of Direct Logic and its applications for the Internet of Things including issues of privacy and security. Then in Part 3, several application areas ranging from law to biology are discussed, as mentioned above.
References:
A. I. Arruda. “Aspects of the historical development of paraconsistent logic” In Paraconsistent Logic: Essays on the Inconsistent Philosophia Verlag. 1989.
Carl Hewitt. “Security without IoT Mandatory Backdoors” HAL. 2015.
https://hal.archives-ouvertes.fr/hal-01152495
Stanisław Jaśkowski. “Propositional calculus for contradictory deductive systems” Studia Logica. 24 (1969) “Rachunek zdań dla systemów dedukcyjnych sprzecznych” in: Studia Societatis Scientiarum Torunensis, Sectio A, Vol. I, No. 5, Toruń 1948.
Graham Priest, and Richard Routley “The History of Paraconsistent Logic” in Paraconsistent Logic: Essays on the Inconsistent Philosophia Verlag. 1989.
1 of 3 people found the following review helpful.
all general statement are false. many general statements are even more false.
By richard w
All general statements are false. If we make several general statements, they will to be false in different ways, and contradict each other. In classical mathematical logic, this means that we can deduce anything. Not good. We can try to resolve the inconsistencies, but if we are working with a crowd-sourced knowledge base with multiple authors, what are the chances? This is the issue that Hewitt and his co-workers have picked up on and run with.
This collection is lively, argumentative, and eclectic, hitting on social networks, legal reasoning, privacy and security, education, biology, medicine, and the Singularity. And some unconventional mathematical logic.
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