A Computational Framework for Practical Social Reasoning

This article describes a framework for practical social reasoning designed to be used for analysis, specification, and implementation of the social layer of agent reasoning in multiagent systems. Our framework, called the expectation strategy behavior (ESB) framework, is based on (i) using sets of update rules for social beliefs tied to observations (so‐called expectations), (ii) bounding the amount of reasoning to be performed over these rules by defining a reasoning strategy, and (iii) influencing the agent's decision‐making logic by means of behaviors conditioned on the truth status of current and future social beliefs. We introduce the foundations of ESB conceptually and present a formal framework and an actual implementation of a reasoning engine, which is specifically combined with a general (belief–desire–intention‐based) practical reasoning programming system. We illustrate the generality of ESB through select case studies, which show that it is able to represent and implement different typical styles of social reasoning. The broad coverage of existing social reasoning methods, the modularity that derives from its declarative nature, and its focus on practical implementation make ESB a useful tool for building advanced socially reasoning agents.     

Process and Policy: Resource-Bounded NonDemonstrative Reasoning

This paper investigates the appropriateness of formal dialectics as a basis for nonmonotonic reasoning and defeasible reasoning that takes computational limits seriously. Rules that can come into conflict should be regarded as policies, which are inputs to deliberative processes. Dialectical protocols are appropriate for such deliberations when resources are bounded and search is serial.
AI, it is claimed here, is now perfectly positioned to correct many misconceptions about reasoning that have resulted from mathematical logic's enormous success in this century: among them, (1) that all reasons are demonstrative, (2) that rational belief is constrained, not constructed, and (3) that process and disputation are not essential to reasoning. AI mainly provides new impetus to formalize the alternative (but older) conception of reasoning, and AI provides mechanisms with which to create compelling formalism that describes the control of processes.
The technical contributions here are: the partial justification of dialectic based on controlling search; the observation that nonmonotonic reasoning can be subsumed under certain kinds of dialectics; the portrayal of inference in knowledge bases as policy reasoning; the review of logics of dialogue and proposed extensions; and the preformal and initial formal discussion of aspects and variations of dialectical systems with nondemonstrative reasons.     

Artificial argument assistants for defeasible argumentation

The present paper discusses experimental argument assistance tools. In contrast with automated reasoning tools, the objective is not to replace reasoning, but to guide the user's production of arguments. Two systems are presented, and based on . The focus is on defeasible argumentation with an eye on the law. Argument assistants for defeasible argumentation naturally correspond to a view of the application of law as dialectical theory construction. The experiments provide insights into the design of argument assistants, and show the pros and cons of different ways of representing argumentative data. The development of the argumentation theories underlying the systems has culminated in the logical system that formalizes the interpretation of prima facie justified assumptions. introduces an innovative use of conditionals expressing support and attack. This allows the expression of warrants for support and attack, making it a transparent and flexible system of defeasible argumentation.     

A theory of defeasible reasoning

Reasoning can lead not only to the adoption of beliefs, but also to the retraction of beliefs. In philosophy, this is described by saying that reasoning is defeasible. My ultimate objective is the construction of a general theory of reasoning and its implementation in an automated reasoner capable of both deductive and defeasible reasoning. the resulting system is named “OSCAR.” This article addresses some of the theoretical underpinnings of OSCAR. This article extends my earlier theory in two directions. First, it addresses the question of what the criteria of adequacy should be for a defeasible reasoner. Second, it extends the theory to accommodate reasons of varying strengths.     

A conditional logic for defeasible beliefs

This paper provides a framework for representing beliefs by distinguishing between (i) the defeasible principles of a belief system, (ii) the propositions that are beyond reasonable doubt in a belief state, and (iii) the propositions ‘favored’ on the basis of defeasible principles and those propositions that are beyond reasonable doubt. Defeasible principles are interpreted semantically by means of a Lewis-style ranking of worlds (without the assumption that the actual world is among the ‘innermost’, or most highly ranked, worlds). The ‘favored closure’ (F-closure) of a set of defeasible principles and reasonable propositions is non-monotonic. Yet, given the concept of ‘pruning’ the default ranking relative to a set of worlds (determined by what is beyond reasonable doubt in a particular belief state) we provide a formal characterization of the conditions under which in inference to a favored conclusion on the basis of defeasible rules and reasonable propositions, is warranted. The adequacy of our representation of defeasible principles can be tested by considering a number of valid formulas that we list. We show that our concept of defeasible principle parallels but is not identical to the concept of ‘relatively high conditional probability’. An example of application of the formal language and semantics is given, and the final parts of the paper contain u     

On Resolving Conflicts Between Arguments

Argument systems are based on the idea that one can construct arguments for propositions—structured reasons justifying the belief in a proposition. Using defeasible rules, arguments need not be valid in all circumstances, therefore, it might be possible to construct an argument for a proposition as well as its negation. When arguments support conflicting propositions, one of the arguments must be defeated, which raises the question of which (sub‐) arguments can be subject to defeat. In legal argumentation, metarules determine the valid arguments by considering the last defeasible rule of each argument involved in a conflict. Since it is easier to evaluate arguments using their last rules, can a conflict be resolved by considering only the last defeasible rules of the arguments involved? We propose a new argument system where, instead of deriving a defeat relation between arguments, arguments for the defeat of defeasible rules are constructed. This system allows us to determine a set of valid (undefeated) arguments in linear time using an algorithm based on a JTMS, allows conflicts to be resolved using only the last rules of the arguments, allows us to establish a relation with Default Logic, and allows closure properties such as cumulativity to be proved. We propose an extension of the argument system based on a proposal for reasoning by cases in default logic.     

Defeasible Logic on an Embedded Microcontroller

Defeasible logic is a system of reasoning in which rules have exceptions, and when rules conflict, the one that applies most specifically to the situation wins out. This paper reports a successful application of defeasible logic to the implementation of an embedded control system. The system was programmed in d-Prolog (a defeasible extension of Prolog), and the inferences were compiled into a truth table that was encoded on a low-end PIC microcontroller.Advantages of defeasible logic include conciseness and correct handling of the passage of time. It is distinct from fuzzy logic and probabilistic logic, addressing a different set of problems.     

Extending abstract argumentation systems theory

In this paper, we extend the theory of abstract argumentation systems proposed by Vreeswijk (1997). This framework stands at a high abstraction level and provides a general model for argumentation activity. However, the theory reveals an inherent limitation in that the premises of the argumentation process are assumed to be indefeasible, and this introduces the need of an implicit constraint on the strength of the arguments, in order to preserve correctness. In many application contexts the information available to start reasoning is not guaranteed to be completely reliable, therefore it is natural to assume that premises can be discarded during the argumentation process. We extend the theory by admitting that premises can be defeated and relaxing the implicit assumption about their strength.Besides fixing the technical problems related to this hidden assumption (e.g., ensuring that warranted arguments are compatible), our proposal provides an integrated model for belief revision and defeasible reasoning, confirming the suitability of argumentation as a general model for the activity of intelligent reasoning in presence of various kinds of uncertainty.     

Default Reasoning as Situated Monotonic Inference*

Since its inception, situation theory has been concerned with the situated nature of meaning and cognition, a theme which has also recently gained some prominence in Artificial Intelligence. Channel theory is a recently developed framework which builds on concepts introduced in situation theory, in an attempt to provide a general theory of information flow. In particular, the channel theoretic framework offers an account of fallible regularities, regularities which provide enough structure to an agent's environment to support efficient cognitive processing but which are limited in their reliability to specific circumstances. This paper describes how this framework can lead to a different perspective on defeasible reasoning: rather than being seen as reasoning with incomplete information, an agent makes use of a situated regularity, choosing to use the regularity that seems best suited (trading off reliability and simplicity) to the circumstances it happens to find itself in. We present a formal model for this task, based on the channel theoretic framework, and sketch how the model may be used as the basis for a methodology of defeasible situated reasoning, whereby agents reason with simple monotonic regularities but may revise their choice of regularity on learning more about their circumstances.     

Towards a Formal Account of Reasoning about Evidence: Argumentation Schemes and Generalisations

This paper studies the modelling of legal reasoning about evidence within general theories of defeasible reasoning and argumentation. In particular, Wigmore's method for charting evidence and its use by modern legal evidence scholars is studied in order to give a formal underpinning in terms of logics for defeasible argumentation. Two notions turn out to be crucial, viz. argumentation schemes and empirical generalisations.     

Proof explanation for a nonmonotonic Semantic Web rules language

In this work, we present the design and implementation of a system for proof explanation in the Semantic Web, based on defeasible reasoning. Trust is a vital feature for Semantic Web. If users (humans and agents) are to use and integrate system answers, they must trust them. Thus, systems should be able to explain their actions, sources, and beliefs. Our system produces automatically proof explanations using a popular logic programming system (XSB), by interpreting the output from the proof’s trace and converting it into a meaningful representation. It also supports an XML representation for agent communication, which is a common scenario in the Semantic Web. In this paper, we present the design and implementation of the system, a RuleML language extension for the representation of a proof explanation, and we give some examples of the system. The system in essence implements a proof layer for nonmonotonic rules on the Semantic Web.     

基于ATMS和证据理论的不确定性推理方法

本文提出了一种新的不确定性推理方法ＨＵＩＭ．这种方法把基于假设的真值维持系统（ＡＴＭＳ）和Ｄｅｍｐｓｔｅｒ—Ｓｈａｆｅｒ的证据理论有机地结合在一起，使得ＡＴＭＳ这种符号代数系统可用来处理以数值形式表示的不确定性信息．将该方法应用于基于规则的系统，可以弥补这类系统在不确定性推理方面所存在的某些不足．     

Perceiving and Reasoning about a Changing World

A rational agent (artificial or otherwise) residing in a complex changing environment must gather information perceptually, update that information as the world changes, and combine that information with causal information to reason about the changing world. Using the system of defeasible reasoning that is incorporated into the OSCAR architecture for rational agents, a set of reason‐schemas is proposed for enabling an agent to perform some of the requisite reasoning. Along the way, solutions are proposed for the Frame Problem, the Qualification Problem, and the Ramification Problem. The principles and reasoning described have all been implemented in OSCAR.     

INCAS: a legal expert system for contract terms in electronic commerce

Electronic commerce is doing business via electronic networks. Paper-based trade documents such as, for example, request for quotation, purchase order or invoice are replaced by electronic messages, in particular Electronic Data Interchange (EDI) messages. These electronic messages are not only transmitted much faster than paper-based documents, but they can also be processed automatically by computers. An example of this automated processing of electronic messages is electronic contracting and negotiation where the actual trade contract is on-line negotiated and concluded via an electronic network. We present the legal expert system INCAS that can provide on-line explanations about the use of Incoterms in trade contracts. Incoterms stipulate which party (buyer or seller) is responsible for arranging and paying transport of the goods, and arranging the documents necessary for this transport (e.g. export and import clearance documents, certification of origin, quality certificates etc.). INCAS is implemented in the programming language Prolog. We also explain how the defeasible reasoning capability of Prolog is essential for modelling the reasoning about the Incoterms.     

SNePSwD: A newcomer to the SNePS family

Abstract

SNePS 2.1 is a knowledge representation and reasoning system that records the dependencies among propositions that are needed to perform a revision of beliefs when a contradiction is detected. The reasoning of SNePS 2.1 is based on a monotonic logic and the system has no provisos for performing an automatic revision of beliefs. In this paper we present SNePSwD that extends the capabilities of SNePS 2.1 along two dimensions: (1) it is able to represent default rules and to perform default reasoning, i.e. the logic underlying SNePSwD is non-monotonic; (2) it accepts the specification of preferences between hypotheses and uses them to decide which hypotheses to discard to resolve a contradiction. This latter possibility allows a semi-automatic contradiction resolution (in some cases, even completely automatic). We discuss the motivations for the creation of SNePSwD, present the form of default rules it uses, discuss the meaning of each of the three kinds of consequence, and describe how preferences can be specified among propositions and how these preferences are used in the process of belief revision. Finally we present examples that illustrate the aspects discussed in the paper.     

Children’s Application of Theory of Mind in Reasoning and Language

Many social situations require a mental model of the knowledge, beliefs, goals, and intentions of others: a Theory of Mind (ToM). If a person can reason about other people’s beliefs about his own beliefs or intentions, he is demonstrating second-order ToM reasoning. A standard task to test second-order ToM reasoning is the second-order false belief task. A different approach to investigating ToM reasoning is through its application in a strategic game. Another task that is believed to involve the application of second-order ToM is the comprehension of sentences that the hearer can only understand by considering the speaker’s alternatives. In this study we tested 40 children between 8 and 10 years old and 27 adult controls on (adaptations of) the three tasks mentioned above: the false belief task, a strategic game, and a sentence comprehension task. The results show interesting differences between adults and children, between the three tasks, and between this study and previous research.     

Exception Handling in Workflow Systems

In this paper, defeasible workflow is proposed as a framework to support exception handling for workflow management. By using the justified ECA rules to capture more contexts in workflow modeling, defeasible workflow uses context dependent reasoning to enhance the exception handling capability of workflow management systems. In particular, this limits possible alternative exception handler candidates in dealing with exceptional situations. Furthermore, a case-based reasoning (CBR) mechanism with integrated human involvement is used to improve the exception handling capabilities. This involves collecting cases to capture experiences in handling exceptions, retrieving similar prior exception handling cases, and reusing the exception handling experiences captured in those cases in new situations.     

A modular translation from defeasible nets to defeasible logics

Abstract

The sceptical inheritance nets introduced in Horty et al. [Proceedings of AAAI-87 (1987):358-363] are translated into a version of Nute's defeasible logic. Moreover this translation is modular in the sense of Thomason and Horty [Non-Monotonic Reasoning. Springer-Verlag (1989):234]. Apart from the importance of relating two nonmonotonic reasoning formalisms, this result shows that the reasoning mechanisms underlying defeasible logic and defeasible nets are the same. Yet they were invented independently and set in totally different contexts. This is perhaps some evidence that the underlying nonmonotonic reasoning mechanism is mainly correct. We also observe that since defeasible logics can contain both absolute and defeasible rules, they provided a uniform setting for considering nets which contain both strict and defeasible arcs.