Vreeswijk, G. (1997). Abstract argumentation systems. Artificial Intelligence 90, 225--279.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....and Prakken and Sartor [21,20] Both are similar to the ambiguity blocking variant of defeasible logic, but their superiority relations are different: the first is argument based instead of rule based, while the second does not deal with teams of rules. The abstract argumentation framework of [24] addresses both strict and defeasible rules, but not defeaters. However, the treatment of strict rules in defeasible arguments is different from that of defeasible logic, and there is no concept of team defeat. There are structural similarities between the definitions of inductive warrant and ....

....both strict and defeasible rules, but not defeaters. However, the treatment of strict rules in defeasible arguments is different from that of defeasible logic, and there is no concept of team defeat. There are structural similarities between the definitions of inductive warrant and warrant in [24] and # # and ###### , but they differ in that acceptability is monotonic in # whereas the corresponding definitions in [24] are antitone. The semantics that results is not sceptical, and more related to stable semantics than Kunen semantics. The framework does have a notion of ultimately defeated ....

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G. Vreeswijk. Abstract Argumentation Systems. Artificial Intelligence, 90 (1997): 225--279.

....OE, and so all arguments for OE are relatively safe, yet a more preferred conclusion is a formula that follows from the intersection of the maximally consistent subsets of Delta. This approach to argumentation has been developed in [3, 29] A number of other approaches to argumentation, including [70, 72, 97], focus on default reasoning by incorporating default connectives (which can be used to build up default statements similar to the default rules in default logic) into their languages together with associated machinery. Argumentation can also be used to handle uncertain information by extending ....

G. Vreeswijk. Abstract argumentation systems. In M de Glas and D Gabbay, editors, Proceedings of the First World Conference on Fundamentals of Artificial Intelligence. Angkor, 1991.

.... for logic programming with default negation [3, 7] some of them equivalent with well known semantics for normal logic programs such as the stable model semantics [9] or the well founded semantics [8] Argumentation semantics are elegant since they can be captured in an abstract framework [7, 3, 19, 12], for which an elegant theory of attack, defence, acceptability, and other notions can be developed, without recourse to the concrete instance of the reasoning formalism at hand. This framework can then be instantiated to various assumption based reasoning formalisms. Similarly, a dialectical ....

....the body of the rule, body(r) Our definition of an argument for an extended logic program is based on [16] Essentially, an argument is a partial proof, resting on a number of assumptions, i.e. a set of default literals. Note that we do not consider priorities of arguments, as used e.g. in [16, 19]. Definition 2 Let P be an extended logic program. An argument for P is a finite sequence A = r1 , rn ] of ground instances of rules In [3, 6] an argument is a set of assumptions; the two approaches are equivalent in that there is an argument with a conclusion L iff there is a set of ....

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G.A.W. Vreeswijk, `Abstract argumentation systems', Artificial Intelligence, 90(1--2), 225--279, (1997).

....must reason on their own mental states in order to build arguments in favor of their future commitments, as well as on other agents commitments in order to be able to take position with regard to the contents of these commitments. The systems proposed in the literature, for example in [13] and [32], do not take into account the arguments which can support actions on commitments. It is these arguments which we define in this section. In fact, before committing to some fact h being true (i.e. before creating a commitment whose content is h) the speaker agent must use its argumentation ....

Vreeswijk, G.A.W. Abstract argumentation systems. Artificial Intelligence, 90 (1-2), 1997, 225-279.

....inductive, abductive, or analogical nature. For the underlying logic, we assume a Prawitz style natural deduction system. Definition 2 (Deductive system) A deductive system S is a pair R# For discussion of abstract argument systems, see Dung [Dun95] Kowalski and Toni [KT96] and Vreeswijk [Vre97] The correspondence is many one: a given argument exchange defines a unique (up to isomorphism) abstract argument system, but a given argument system may allow for for several possible temporal unfoldings. cf. Prawitz [Pra65] details of the exposition are based on Tennant [Ten78] and ....

G. A. W. Vreeswijk. Abstract argumentation systems. Artificial Intelligence, 90:225--279, 1997. 34

.... to any particular criterion for the computation of the strength of arguments, we only assume that any argument cannot be strictly stronger that any of its subarguments: ## # sub#### strength### # strength### (1) This condition, corresponding to one of the three axioms on strength introduced in [15], is sufficiently general to ensure that no interesting distribution of strength is excluded beforehand. The strength of the arguments plays a role in the determination of the attack relation between arguments, namely in an inference graph ## # ## # ## # ## ## # we have that # ## # ### # ## # ### ....

G. A. W. Vreeswijk. Abstract argumentation systems. Artificial Intelligence, 90(1--2):225--279, 1997.

....DL can be described informally in terms of arguments, the logic has been formalized in a proof theoretic setting in which arguments play no role. In this paper we will provide an argumentationtheoretic semantics for DL. There are already several different abstract argumentation frameworks [10, 8, 15, 20, 23, 24]. However, DL provides several challenges that have not yet been addressed by this work: 1) DL has a directly sceptical semantics, in the sense of Horty [14] also called conservative in Wagner s classification [25] Most argumentation theoretic approaches provide sceptical semantics as the ....

....DL [18] The correctness of the mapping needs to be established if [16] is to be applied to an existing language like DL. In fact the representation of priorities is inappropriate for DL, although results of [3, 1] might be adapted to remedy this point. The abstract argumentation framework of [24] addresses both strict and defeasible rules, but not defeaters. However, the treatment of strict rules in defeasible arguments is different from that of DL, and there is no concept of team defeat. There are structural similarities between the definitions of inductive warrant and warrant in [24] ....

[Article contains additional citation context not shown here]

G. Vreeswijk. Abstract Argumentation Systems. Artificial Intelligence, 90 (1997): 225--279.

....and Prakken and Sartor [21, 20] Both are similar to the ambiguity blocking variant of defeasible logic, but their superiority relations are different: the first is argument based instead of rule based, while the second does not deal with teams of rules. The abstract argumentation framework of [24] addresses both strict and defeasible rules, but not defeaters. However, the treatment of strict rules in defeasible arguments is different from that of defeasible logic, and there is no concept of team defeat. There are structural similarities between the definitions of inductive warrant and ....

....both strict and defeasible rules, but not defeaters. However, the treatment of strict rules in defeasible arguments is different from that of defeasible logic, and there is no concept of team defeat. There are structural similarities between the definitions of inductive warrant and warrant in [24] and J i and JArgsD , but they differ in that acceptability is monotonic in S whereas the corresponding definitions in [24] are antitone. The semantics that results is not sceptical, and more related to stable semantics than Kunen semantics. The framework does have a notion of ultimately defeated ....

[Article contains additional citation context not shown here]

G. Vreeswijk. Abstract Argumentation Systems. Artificial Intelligence, 90 (1997): 225--279.

....imply , and so all arguments for are relatively safe, yet a more preferred conclusion is a formula that follows from the intersection of the maximally consistent subsets of . This approach to argumentation has been developed in [3, 29] A number of other approaches to argumentation, including [70, 72, 97], focus on default reasoning by incorporating default connectives (which can be used to build up default statements similar to the default rules in default logic) into their languages together with associated machinery. Argumentation can also be used to handle uncertain information by extending ....

G. Vreeswijk. Abstract argumentation systems. In M de Glas and D Gabbay, editors, Proceedings of the First World Conference on Fundamentals of Articial Intelligence. Angkor, 1991.

....allows the system to reason about, store updated views of the participants, and draw inferences without believing in what the participants believe. The research will address important issues involving interactive argumentation systems. It will attempt to combine formal techniques in argumentation (Vreeswijk, 1997; Loui and Norman, 1993) and those that focus on generating effective arguments (Grasso, 1998; Zukerman et al. 1998; Reed et al. 1996) Issues involving model acquisition, knowledge representation, and inferencing techniques in a natural language based argumentation framework using dynamic ....

Vreeswijk, G. (1997). Abstract argumentation systems. Artificial Intelligence 90(1-2):225--279.

....In cases where information is lacking, one can do as well as possible by arguing on the basis of only that information which is available. This approach to argumentation has received some attention within the Artificial Intelligence community, for example in the work of Loui (1993) and Vreeswijk (1997), and we believe it has considerable further potential in applications intended for practical reasoning. A related question for implementation of effective decision support systems will be that of the computational complexity of any decision calculi and inference algorithms used within the ....

Vreeswijk, Gerard A.W. (1997). "Abstract argumentation systems". Artificial Intelligence, Vol. 90, pp. 225-279.

....be described informally in terms of arguments, the logic has been formalized in a proof theoretic setting in which arguments play no role. In this paper we will provide an argumentation theoretic semantics for defeasible logic. There are already several different abstract argumentation frameworks [9, 7, 13, 18, 21, 22]. However, defeasible logic provides several challenges that have not yet been addressed by this work: 1) Defeasible logic has a directly sceptical semantics, in the sense of Horty [12] also called conservative in Wagner s classification [23] Most argumentation theoretic approaches provide ....

....of the mapping needs to be established if [14] is to be applied to an existing language like defeasible logic. In fact the representation of priorities is inappropriate for defeasible logic, although results of [2, 1] might be adapted to remedy this point. The abstract argumentation framework of [22] addresses both strict and defeasible rules, but not defeaters. However, the treatment of strict rules in defeasible arguments is different from that of defeasible logic, and there is no concept of team defeat. There are structural similarities between the definitions of inductive warrant and ....

[Article contains additional citation context not shown here]

G. Vreeswijk. Abstract Argumentation Systems. Artificial Intelligence, 90 (1997): 225--279.

....they observe movements of the market over time. They also su ested that a cooperative multia ent system, with a simple communication mechanism of explicit hint exchan e between a ents, achieves a further increase in performance. There are several related work in argumentation and defeasible logic [1, 10, 15, 21, 22, 2]. However, as far as we know, usingargumentation for stock market agents was not considered in previous approachs. The interested reader is referred to the followingsurveys in defeasible argumentation: 14, 3] We are workingnow in the development of a more robust, e#cient and fast system for ....

Gerard A.W. Vreeswijk. Abstract argumentation systems. Artificial Intelligence, 90:225--279, 1997.

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G.A.W. Vreeswijk, `Abstract argumentation systems', Artificial Intelligence, 90, 225--279, (1997).

....and will therefore be used as a running example throughout this paper. a b c d e h g p i j k l m n f q Fig. 1. Attack relations in the running example. In practical applications it is necessary to further specify the internal structure of the arguments and the relation . See e.g. [30]. However, for the purpose of this paper it not necessary to do so; at present it suces to know that there are arguments, and that some arguments attack other arguments. The output of the system is one or more argument extensions, which are sets of arguments that represent a maximally defendable ....

G.A.W. Vreeswijk. Abstract argumentation systems. Articial Intelligence, 90:225-279, 1997.

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Vreeswijk, G. (1997). Abstract argumentation systems. Artificial Intelligence 90, 225--279.

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G. Vreeswijk. Abstract argumentation systems. Artif. Intell., 90(1-2):225--279, 1997.

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G. A. Vreeswijk. Abstract argumentation systems. Artificial Intelligence, 90:225--279, 1997.

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Vreeswijk, Gerard A. W. (1997). Abstract argumentation systems. Artificial intelligence, 90, 225--279.

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Gerard A.W. Vreeswijk. Abstract argumentation systems. Artificial Intelligence, 90:225--279, 1997.

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VREESWIJK G. A., "Abstract Argumentation Systems", Artificial Intelligence, vol. 90, 1997, p. 225-279.

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G. Vreeswijk. Abstract argumentation systems. Artif. Intell., 90(1-2):225--279, 1997.

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Vreeswijk, G.A.W. Abstract argumentation systems. Artificial Intelligence, 90 (1-2), 1997, 225-279.

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G. Vreeswijk. Abstract argumentation systems. Artificial Intelligence, 90:225--279, 1997.

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G Vreeswijk. Abstract argumentation systems. Artificial Intelligence, 90:225--279, 1997.

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