Pierre Marquis

A knowledge compilation map

We propose a perspective on knowledge compilation which calls for analyzing different compilation approaches according to two key dimensions: the succinctness of the target compilation language, and the class of queries and transformations that the language supports in polytime. We then provide a knowledge compilation map, which analyzes a large number of existing target compilation languages according to their succinctness and their polytime transformations and queries. We argue that such analysis is necessary for placing new compilation approaches within the context of existing ones. We also go beyond classical, flat target compilation languages based on CNF and DNF, and consider a richer, nested class based on directed acyclic graphs (such as OBDDs), which we show to include a relatively large number of target compilation languages.

Consistency restoriation and explanations in dynamic CSPs----application to configuration

Most of the algorithms developed within the Constraint Satisfaction Problem (CSP) framework cannot be used as such to solve interactive decision support problems, like product configuration. Indeed, in such problems, the user is in charge of assigning values to variables. Global consistency maintaining is only one among several functionalities that should be offered by a CSP-based platform in order to help the user in her task; other important functionalities include providing explanations for some users choices and ways to restore consistency.

Consequence finding algorithms

In this section, the notion of consequence finding is introduced and motivated in informal terms. Then, the scope of the chapter and its organization are successively pointed out.

Symmetric argumentation frameworks

This paper is centered on the family of Dungs finite argumentation frameworks when the attacks relation is symmetric (and nonempty and irreflexive). We show that while this family does not contain any well-founded framework, every element of it is both coherent and relatively grounded. Then we focus on the acceptability problems for the various semantics introduced by Dung, yet generalized to sets of arguments. We show that only two distinct forms of acceptability are possible when the considered frameworks are symmetric. Those forms of acceptability are quite simple, but tractable; this contrasts with the general case for which all the forms of acceptability are intractable (except for the ones based on grounded or naive extensions).

Prudent semantics for argumentation frameworks

We present new prudent semantics within Dungs theory of argumentation. Under such prudent semantics, two arguments cannot belong to the same extension whenever one of them attacks indirectly the other one. We argue that our semantics lead to a better handling of controversial arguments than Dungs ones. We compare the prudent inference relations induced by our semantics w.r.t. cautiousness; we also compare them with the inference relations induced by Dungs semantics

The strategy-proofness landscape of merging

Merging operators aim at defining the beliefs/goals of a group of agents from the beliefs/goals of each member of the group. Whenever an agent of the group has preferences over the possible results of the merging process (i.e., the possible merged bases), she can try to rig the merging process by lying on her true beliefs/goals if this leads to a better merged base according to her point of view. Obviously, strategy-proof operators are highly desirable in order to guarantee equity among agents even when some of them are not sincere. In this paper, we draw the strategy-proof landscape for many merging operators from the literature, including model-based ones and formula-based ones. Both the general case and several restrictions on the merging process are considered.

Reasoning under inconsistency: A forgetting-based approach

In this paper, a fairly general framework for reasoning from inconsistent propositional bases is defined. Variable forgetting is used as a basic operation for weakening pieces of information so as to restore consistency. The key notion is that of recoveries, which are sets of variables whose forgetting enables restoring consistency. Several criteria for defining preferred recoveries are proposed, depending on whether the focus is laid on the relative relevance of the atoms or the relative entrenchment of the pieces of information (or both). Our framework encompasses several previous approaches as specific cases, including reasoning from preferred consistent subsets, and some forms of information merging. Interestingly, the gain in flexibility and generality offered by our framework does not imply a complexity shift compared to these specific cases.

Extending abduction from propositional to first-order logic

Abduction is often considered as inference to the best explanation. In this paper, we appeal to abduction as a way to generate all but only explanations that have “some reasonable prospect” of being valid.

Conditional independence in propositional logic

Independence-the study of what is relevant to a given problem of reasoning--is an important AI topic. In this paper, we investigate several notions of conditional independence in propositional logic: Darwiche and Pearls conditional independence, and some more restricted forms of it. Many characterizations and properties of these independence relations are provided. We show them related to many other notions of independence pointed out so far in the literature (mainly formula-variable independence, irrelevance and novelty under various forms, separability, interactivity). We identify the computational complexity of conditional independence and of all these related independence relations.

Extending Classical Planning to the Multi-agent Case: A Game-Theoretic Approach

When several agents operate in a common environment, their plans may interfere so that the predicted outcome of each plan may be altered, even if it is composed of deterministic actions, only. Most of the multi-agent planning frameworks either view the actions of the other agents as exogeneous events or consider goal sharing cooperative agents. In this paper, we depart from such frameworks and extend the well-known single agent framework for classical planning to a multi-agent one. Focusing on the two agents case, we show how valuable plans can be characterized using game-theoretic notions, especially Nash equilibrium.