By Douglas Walton (auth.), Peter McBurney, Iyad Rahwan, Simon Parsons, Nicolas Maudet (eds.)
This ebook constitutes the completely refereed court cases of the sixth overseas Workshop on Argumentation in Multi-Agent platforms, held in Budapest, Hungary, in might 2009, in organization with the eighth foreign convention on self sufficient brokers and Multi-Agent structures (AAMAS 2009). The 18 revised complete papers have been conscientiously reviewed and chosen from a number of submissions and are geared up in 4 topical sections on functional reasoning and argument approximately motion; persuasion and negotiation; argumentation idea; and functions and feelings.
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Additional resources for Argumentation in Multi-Agent Systems: 6th International Workshop, ArgMAS 2009, Budapest, Hungary, May 12, 2009. Revised Selected and Invited Papers
A. Matt, F. R. Vaccari – A ⊆ L, referred to as the set of assumptions – C : A → L, referred to as the contrary mapping As in [13,10], we will restrict attention to flat ABA frameworks, such that if n ∈ R for any n ≥ 0. p l Arguments are deductions of conclusions supported by assumptions. Arguments can be represented as trees having conclusions as their roots and assumptions as their leaves . These trees can be computed in a forward or backward manner. If computed backwards, an argument A p with conclusion p ∈ L and supported by the set of assumptions A ⊆ A is a ﬁnite sequence of multisets of sentences S1 , .
26 A. Belesiotis, M. Rovatsos, and I. Rahwan Each Successor State axiom (Ass ) describes the conditions that should hold in situation s so that a relational or functional ﬂuent takes a certain value in the situation do(a, s), which follows from the application of action a in s. , xn , s) A plan in the situation calculus is treated as an executable situation that satisﬁes a goal statement. Definition 1. do(a, s∗ ) sπ ⊃ Poss(a, s∗ ). Definition 2. A planning problem P is a tuple D, G , where D is a basic action theory denoting the planning domain and G is a ﬂuent sentence specifying the goal.
In section 3 we describe the kind of decision problems we consider in this paper and the notion of dominance to characterise the “best” decisions amongst a set of possible ones. In section 4 we propose a special family of ABA frameworks suitable for representing and reasoning about the beneﬁts of decisions. We also prove that, within the family of frameworks considered, the notion of dominance is equivalent to the semantics of admissibility in argumentation. Section 5 discusses the use of degrees of admissibility as a low complexity heuristic for assessing the “value” of decisions and for ranking them from “best” to “worst”.
Argumentation in Multi-Agent Systems: 6th International Workshop, ArgMAS 2009, Budapest, Hungary, May 12, 2009. Revised Selected and Invited Papers by Douglas Walton (auth.), Peter McBurney, Iyad Rahwan, Simon Parsons, Nicolas Maudet (eds.)