Probabilistic single function dual process theory and logic programming as approaches to non-monotonicity in human vs. artificial reasoning

In this paper, it is argued that single function dual process theory is a more credible psychological account of non-monotonicity in human conditional reasoning than recent attempts to apply logic programming (LP) approaches in artificial intelligence to these data. LP is introduced and among other critiques, it is argued that it is psychologically unrealistic in a similar way to hash coding in the classicism vs. connectionism debate. Second, it is argued that causal Bayes nets provide a framework for modelling probabilistic conditional inference in System 2 that can deal with patterns of inference LP cannot. Third, we offer some speculations on how the cognitive system may avoid problems for System 1 identified by Fodor in 1983. We conclude that while many problems remain, the probabilistic single function dual processing theory is to be preferred over LP as an account of the non-monotonicity of human reasoning

Language generation module for conversational systems

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.Includes bibliographical references (p. 127-132).by Lauren M. Baptist.Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000

Active Logics: A Unified Formal Approach to Episodic Reasoning

Artificial intelligence research falls roughly into two categories: formal and implementational. This division is not completely firm: there are implementational studies based on (formal or informal) theories (e.g., CYC, SOAR, OSCAR), and there are theories framed with an eye toward implementability (e.g., predicate circumscription). Nevertheless, formal/theoretical work tends to focus on very narrow problems (and even on very special cases of very narrow problems) while trying to get them ``right'' in a very strict sense, while implementational work tends to aim at fairly broad ranges of behavior but often at the expense of any kind of overall conceptually unifying framework that informs understanding. It is sometimes urged that this gap is intrinsic to the topic: intelligence is not a unitary thing for which there will be a unifying theory, but rather a ``society'' of subintelligences whose overall behavior cannot be reduced to useful characterizing and predictive principles. Here we describe a formal architecture that is more closely tied to implementational constraints than is usual for formalisms, and which has been used to solve a number of commonsense problems in a unified manner. In particular, we address the issue of formal, integrated, and longitudinal reasoning: inferentially-modeled behavior that incorporates a fairly wide variety of types of commonsense reasoning within the context of a single extended episode of activity requiring keeping track of ongoing progress, and altering plans and beliefs accordingly. Instead of aiming at optimal solutions to isolated, well-specified and temporally narrow problems, we focus on satisficing solutions to under-specified and temporally-extended problems, much closer to real-world needs. We believe that such a focus is required for AI to arrive at truly intelligent mechanisms with the ability to behave effectively over considerably longer time periods and range of circumstances than is common in AI today. While this will surely lead to less elegant formalisms, it also surely is requisite if AI is to get fully out of the blocks-world and into the real world. (Also cross-referenced as UMIACS-TR-99-65

A methodology for the selection of a paradigm of reasoning under uncertainty in expert system development

The aim of this thesis is to develop a methodology for the selection of a paradigm of reasoning under uncertainty for the expert system developer. This is important since practical information on how to select a paradigm of reasoning under uncertainty is not generally available. The thesis explores the role of uncertainty in an expert system and considers the process of reasoning under uncertainty. The possible sources of uncertainty are investigated and prove to be crucial to some aspects of the methodology. A variety of Uncertainty Management Techniques (UMTs) are considered, including numeric, symbolic and hybrid methods. Considerably more information is found in the literature on numeric methods, than the latter two. Methods that have been proposed for comparing UMTs are studied and comparisons reported in the literature are summarised. Again this concentrates on numeric methods, since there is more literature available. The requirements of a methodology for the selection of a UMT are considered. A manual approach to the selection process is developed. The possibility of extending the boundaries of knowledge stored in the expert system by including meta-data to describe the handling of uncertainty in an expert system is then considered. This is followed by suggestions taken from the literature for automating the process of selection. Finally consideration is given to whether the objectives of the research have been met and recommendations are made for the next stage in researching a methodology for the selection of a paradigm of reasoning under uncertainty in expert system development

Disjunctive argumentation semantics (DAS) for reasoning over distributed uncertain knowledge.

by Benson, Ng Hin Kwong.Thesis (M.Phil.)--Chinese University of Hong Kong, 1998.Includes bibliographical references (leaves 111-117).Abstract also in Chinese.Chapter 1 --- Introduction --- p.9Chapter 1.1 --- Our approach --- p.11Chapter 1.2 --- Organization of the thesis --- p.12Chapter 2 --- Logic Programming --- p.13Chapter 2.1 --- Logic programming in Horn clauses --- p.14Chapter 2.1.1 --- Problem with incomplete information --- p.15Chapter 2.1.2 --- Problem with inconsistent information --- p.15Chapter 2.1.3 --- Problem with indefinite information --- p.16Chapter 2.2 --- Logic programming in non-Horn clauses --- p.16Chapter 2.2.1 --- Reasoning under incomplete information --- p.17Chapter 2.2.2 --- Reasoning under inconsistent information --- p.17Chapter 2.2.3 --- Reasoning under indefinite information --- p.20Chapter 2.3 --- "Coexistence of incomplete, inconsistent and indefinite information" --- p.21Chapter 2.4 --- Stable semantics --- p.22Chapter 2.5 --- Well-founded semantics --- p.23Chapter 2.6 --- Chapter summary --- p.25Chapter 3 --- Argumentation --- p.26Chapter 3.1 --- Toulmin's informal argumentation model --- p.27Chapter 3.2 --- Rescher's formal argumentation model --- p.28Chapter 3.3 --- Argumentation in AI research --- p.30Chapter 3.3.1 --- Poole's Logical Framework for Default Reasoning --- p.30Chapter 3.3.2 --- Inheritance Reasoning Framework of Touretzky et. al --- p.31Chapter 3.3.3 --- Pollock's Theory of Defeasible Reasoning --- p.32Chapter 3.3.4 --- Dung's Abstract Argumentation Framework --- p.33Chapter 3.3.5 --- Lin and Shoham's Argument System --- p.35Chapter 3.3.6 --- Vreeswijk's Abstract Argumentation --- p.35Chapter 3.3.7 --- Kowalski and Toni's Uniform Argumentation --- p.36Chapter 3.3.8 --- John Fox's Qualitative Argumentation --- p.37Chapter 3.3.9 --- Thomas Gordon's Pleading Games --- p.38Chapter 3.3.10 --- Chris Reed's Persuasive Dialogue --- p.39Chapter 3.3.11 --- Ronald Loui's Argument Game --- p.39Chapter 3.3.12 --- "Verheij's Reason-Based, Logics and CumulA" --- p.40Chapter 3.3.13 --- Prakken's Defeasible Argumentation --- p.40Chapter 3.3.14 --- Summary of existing frameworks --- p.41Chapter 3.4 --- Chapter summary --- p.42Chapter 4 --- Disjunctive Argumentation Semantics I --- p.46Chapter 4.1 --- Background --- p.47Chapter 4.2 --- Definition --- p.48Chapter 4.3 --- Conflicts within a KBS --- p.52Chapter 4.4 --- Conflicts between KBSs --- p.54Chapter 4.4.1 --- Credulous View --- p.56Chapter 4.4.2 --- Skeptical View --- p.57Chapter 4.4.3 --- Generalized Skeptical View --- p.58Chapter 4.5 --- Semantics --- p.60Chapter 4.6 --- Dialectical proof theory --- p.61Chapter 4.7 --- Relation to existing framework --- p.61Chapter 4.8 --- Issue on paraconsistency --- p.63Chapter 4.9 --- An illustrative example --- p.63Chapter 4.10 --- Chapter summary --- p.65Chapter 5 --- Disjunctive Argumentation Semantics II --- p.67Chapter 5.1 --- Background --- p.68Chapter 5.2 --- Definition --- p.70Chapter 5.2.1 --- Rules --- p.70Chapter 5.2.2 --- Splits --- p.71Chapter 5.3 --- Conflicts --- p.74Chapter 5.3.1 --- Undercut conflicts --- p.75Chapter 5.3.2 --- Rebuttal conflicts --- p.76Chapter 5.3.3 --- Thinning conflicts --- p.78Chapter 5.4 --- Semantics --- p.80Chapter 5.5 --- Relation to existing frameworks --- p.81Chapter 5.6 --- Issue on paraconsistency --- p.82Chapter 5.7 --- An illustrative example --- p.83Chapter 5.8 --- Chapter summary --- p.85Chapter 6 --- Evaluation --- p.86Chapter 6.1 --- Introduction --- p.86Chapter 6.2 --- Methodology --- p.87Chapter 6.3 --- DAS I --- p.88Chapter 6.3.1 --- Inoue's Benchmark problems --- p.88Chapter 6.3.2 --- Sherlock Holmes' problems --- p.96Chapter 6.4 --- DAS II --- p.100Chapter 6.4.1 --- Inoue's benchmark problems --- p.100Chapter 6.4.2 --- Sherlock Holmes' problem --- p.103Chapter 6.5 --- Analysis --- p.103Chapter 6.5.1 --- Possible extension --- p.104Chapter 6.6 --- Chapter summary --- p.106Chapter 7 --- Conclusion --- p.108Chapter 7.0.1 --- Possible extension of the present work --- p.109Bibliography --- p.117Chapter A --- First Oreder Logic (FOL) --- p.118Chapter B --- DAS-I Proof --- p.121Chapter B.1 --- Monotone proof --- p.121Chapter B.2 --- Soundness proof --- p.122Chapter B.3 --- Completeness proof --- p.123Chapter C --- Sherlock Holmes' Silver Blaze Excerpts --- p.125Chapter C.1 --- Double life --- p.125Chapter C.2 --- Poison stable boy --- p.12

International Workshop on Description Logics : Bonn, May 28/29, 1994

This collection of papers forms the permanent record of the 1994 Description Logic Workshop, that was held at the Gustav Stresemann Institut in Bonn, Germany on 28 and 29 May 1994, immediately after the Fourth International Conference on Principles of Knowledge Representation and Reasoning. The workshop was set up to be as informal as possible, so this collection cannot hope to capture the discussions associated with the workshop. However, we hope that it will serve to remind participants of their discussion at the workshop, and provide non-participants with indications of the topics that were discussed at the workshop. The workshop consisted of seven regular sessions and one panel session. Each regular session had about four short presentations on a single theme, but also had considerable time reserved for discussion. The themes of the sessions were Foundations of Description Logics, Architecture of Description Logics and Description Logic Systems, Language Extensions, Expanding Description Logics, General Applications of Description Logics, Natural Language Applications of Description Logics, Connections between Description Logics and Databases, and the Future of Description Logics and Description Logic Systems. The session on Foundations of Description Logics concentrated on computational properties of description logics, correspondences between description logics and other formalisms, and on semantics of description logics, Similarly, there is discussion on how to develop tractable desription logics, for some notion of tractable, and whether it is useful to worry about achieving tractability at all. Several of the participants argued in favour of a very expressive description logic. This obviously precludes tractability or even decidability of complete reasoning. Klaus Schild proposed that for some purposes one could employ "model checking" (i .e., a closed world assumption) instead of "theorem proving," and has shown that this is still tractable for very large languages. Maurizio Lenzerini\u27s opinion was that it is important to have decidable languages. Tractability cannot be achieved in several application areas because there one needs very expressive constructs: e.g., axioms, complex role constructors, and cycles with fixed-point semantics. For Bob MacGregor, not even decidability is an issue since he claims that Loom\u27s incomplete reasoner is sufficient for his applications. The discussion addressed the question of whether there is still need for foundations, and whether the work on foundation done until now really solved the problems that the designers of early DL systems had. Both questions were mostly answered in the affirmative, with the caveat that new research on foundations should make sure that it is concerned with "real" problems, and not just generates new problems. In the session on Architecture of Description Logics and Description Logic Systems the participants considered different ways of putting together description logics and description logic systems. One way of doing this is to have a different kind of inference strategy for description logics, such as one based on intuitionistic logics or one based directly on rules of inference-thus allowing variant systems. Another way of modifying description logic systems is to divide them up in different ways, such as making a terminology consist of a schema portion and a view portion. Some discussion in this session concerned whether architectures should be influenced by application areas, or even by particular applications. There was considerable discussion at the workshop on how Description Logics should be extended or expanded to make them more useful. There are several methods to do this. The first is to extend the language of descriptions, e.g ., to represent n-ary relations, temporal information, or whole-part relationships, all of which were discussed at the workshop. The second is to add in another kind of reasoning, such as default reasoning, while still keeping the general framework of description logic reasoning. The third is to incorporate descriptions or description-like constructs in a larger reasoner, such as a first order reasoner. This was the approach taken in OMEGA and is the approach being taken in the Loom project. There have been many extensions of the first two kinds proposed for description logics, including several presented at the workshop. One quest ion discussed at the workshop was whether these extensions fit in well with the philosophy of description logic. Another question was whether the presence of many proposals for extensions means that description logics are easy to expand, or that description logics are inadequate representation formalisms? The general consensus was that description logics adequately capture a certain kind of core reasoning and that they lend themselves to incorporation with other kinds of reasoning. Care must be taken, however, to keep the extended versions true to the goals of description logics. The sessions on Applications of Description Logics had presentations on applications of description logics in various areas, including configuration, tutoring, natural language processing, and domain modeling. Most of these applications are research applications, funded by government research programs. There was discussion of what is needed to have more fielded applications of description logics. The session on Connections between Description Logics and Databases considered three kinds of connections between Description Logics and Databases: 1. using Description Logics for expressing database schemas, including local schemas, integrated schemas, and views, integrity constraints, and queries; 2. using Description Logic reasoning for various database-related reasoning, including schema integration and validation, and query optimization, and query validation and organization; and 3. making Description Logic reasoners more like Database Mangagement Systems via optimization. All three of these connections are being actively investigated by the description logic community. The panel session on the Future of Description Logics and Description Logic Systems discussed where the future of description logics will lie. There seems to be a consensus that description logics must forge tighter connections with other formalisms, such as databases or object-oriented systems. In this way, perhaps, description logics will find more real applications