Marcelo A. Falappa

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We present different constructions for non-prioritized belief revision, that is, belief changes in which the input sentences are not always accepted. First, we present the concept of explanation in a deductive way. Second, we define multiple revision operators with respect to sets of sentences (representing explanations), giving representation theorems.(More)
Five types of constructions are introduced for non-prioritized belief revision, i.e., belief revision in which the input sentence is not always accepted. These constructions include generalizations of entrenchment-based and sphere-based revision. Axiomatic characterizations are provided, and close interconnections are shown to hold between the di®erent(More)
We propose an abstract argumentation theory whose dynamics is captured by the application of belief revision concepts. The theory is deemed as abstract because both the underlying logic for arguments and argumentative semantics remain unspecified. Regarding our approach to argument theory change, we define some basic change operations along with their(More)
Argument Theory Change applies classic belief change concepts to the area of argumentation. This intersection of fields takes advantage of the definition of a Dynamic Abstract Argumentation Framework, in which an argument is either active or inactive, and only in the former case it is taken into consideration in the reasoning process. An approach for an(More)
This work elaborates on the connection between partial meet contractions and kernel contractions in belief change theory. We present a way to define incision functions (used in kernel contractions) from selection functions (used in partial meet contractions) and vice versa. Then we make precise under which conditions there are exact correspondences between(More)
We discuss the value of argumentation in reaching agreements, based on its capability for dealing with conflicts and uncertainty. Logic-based models of argumentation have recently emerged as a key topic within Artificial Intelligence. Key reasons for the success of these models is that they are akin to human models of reasoning and debate, and their(More)
In real-world applications, knowledge bases consisting of all the available information for a specific domain, along with the current state of affairs, will typically contain contradictory data, coming from different sources, as well as data with varying degrees of uncertainty attached. An important aspect of the effort associated with maintaining such(More)
The BDI model provides what it is possibly one of the most promising architectures for the development of intelligent agents, and has become one of the most studied and well known in the literature. The basic BDI model needs to be complemented with two mechanisms: one for reasoning about intentions, and one for revising beliefs upon perception. In this(More)