3,338 research outputs found
Non-normal modalities in variants of Linear Logic
This article presents modal versions of resource-conscious logics. We
concentrate on extensions of variants of Linear Logic with one minimal
non-normal modality. In earlier work, where we investigated agency in
multi-agent systems, we have shown that the results scale up to logics with
multiple non-minimal modalities. Here, we start with the language of
propositional intuitionistic Linear Logic without the additive disjunction, to
which we add a modality. We provide an interpretation of this language on a
class of Kripke resource models extended with a neighbourhood function: modal
Kripke resource models. We propose a Hilbert-style axiomatization and a
Gentzen-style sequent calculus. We show that the proof theories are sound and
complete with respect to the class of modal Kripke resource models. We show
that the sequent calculus admits cut elimination and that proof-search is in
PSPACE. We then show how to extend the results when non-commutative connectives
are added to the language. Finally, we put the logical framework to use by
instantiating it as logics of agency. In particular, we propose a logic to
reason about the resource-sensitive use of artefacts and illustrate it with a
variety of examples
Developing a corpus of strategic conversation in The Settlers of Catan
International audienceWe describe a dialogue model and an implemented annotation scheme for a pilot corpus of annotated online chats concerning bargaining negotiations in the game The Settlers of Catan. We will use this model and data to analyze how conversations proceed in the absence of strong forms of cooperativity, where agents have diverging motives. Here we concentrate on the description of our annotation scheme for negotiation dialogues, illustrated with our pilot data, and some perspectives for future research on the issue
Logics for modelling collective attitudes
We introduce a number of logics to reason about collective propositional
attitudes that are defined by means of the majority rule. It is well known that majoritarian
aggregation is subject to irrationality, as the results in social choice theory and judgment
aggregation show. The proposed logics for modelling collective attitudes are based on
a substructural propositional logic that allows for circumventing inconsistent outcomes.
Individual and collective propositional attitudes, such as beliefs, desires, obligations, are
then modelled by means of minimal modalities to ensure a number of basic principles. In
this way, a viable consistent modelling of collective attitudes is obtained
Modelling Multilateral Negotiation in Linear Logic
We show how to embed a framework for multilateral negotiation,
in which a group of agents implement a sequence of deals
concerning the exchange of a number of resources, into linear logic.
In this model, multisets of goods, allocations of resources, preferences
of agents, and deals are all modelled as formulas of linear logic.
Whether or not a proposed deal is rational, given the preferences of
the agents concerned, reduces to a question of provability, as does
the question of whether there exists a sequence of deals leading to an
allocation with certain desirable properties, such as maximising social
welfare. Thus, linear logic provides a formal basis for modelling
convergence properties in distributed resource allocation
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A theoretical framework for computer models of cooperative dialogue, acknowledging multi-agent conflict
This thesis describes a theoretical framework for modelling cooperative dialogue. The linguistic theory is a version of speech act theory adopted from Cohen and Levesque, in which dialogue utterances are generated and interpreted pragmatically in the context of a theory of rational interaction. The latter is expressed as explicitly and formally represented principles of rational agenthood and cooperative interaction. The focus is the development of strategic principles of multi-agent interaction as such a basis for cooperative dialogue. In contrast to the majority of existing work, these acknowledge the Positive role of conflict to multi-agent cooperation. and make no assumptions regarding the benevolence and sincerity of agents. The result is a framework wherein agents can resolve conflicts by negotiation. It is a preliminary stage to the future building of computer models of cooperative dialogue for both HCI and DAI, which will therefore be more widely and generally applicable than those currently in existence.
The theory of conflict and cooperation is expressed in the different patterns of mental states which characterise multi-agent conflict, cooperation and indifference as three alternative postural relations. Agents can recognise and potentially create these. Dialogue actions are the strategic tools with which mental states can be manipulated, whilst acknowledging that agents are autonomous over their mental states; they have control over what they acquire and reveal in dialogue. Strategic principles of belief and goal adoption are described in terms of the relationships between autonomous agents' beliefs, goals, preferences, and interests, and the relation of these to action. Veracity, mendacity, concealing and revealing are defined as properties of acts. The role of all these elements in reasoning about dialogue action and conflict resolution, is tester in analyses of two example dialogues; a record of a real trade union negotiation and an extract from "Othello" by Shakespeare
Weighted logics for artificial intelligence : an introductory discussion
International audienceBefore presenting the contents of the special issue, we propose a structured introductory overview of a landscape of the weighted logics (in a general sense) that can be found in the Artificial Intelligence literature, highlighting their fundamental differences and their application areas
Preferential Multi-Context Systems
Multi-context systems (MCS) presented by Brewka and Eiter can be considered
as a promising way to interlink decentralized and heterogeneous knowledge
contexts. In this paper, we propose preferential multi-context systems (PMCS),
which provide a framework for incorporating a total preorder relation over
contexts in a multi-context system. In a given PMCS, its contexts are divided
into several parts according to the total preorder relation over them,
moreover, only information flows from a context to ones of the same part or
less preferred parts are allowed to occur. As such, the first preferred
parts of an PMCS always fully capture the information exchange between contexts
of these parts, and then compose another meaningful PMCS, termed the
-section of that PMCS. We generalize the equilibrium semantics for an MCS to
the (maximal) -equilibrium which represents belief states at least
acceptable for the -section of an PMCS. We also investigate inconsistency
analysis in PMCS and related computational complexity issues
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