Extending Propositional Logic with Concrete Domains for Multi-issue Bilateral Negotiation

Abstract

We present a novel approach to knowledge-based automated one-shot multi-issue bilateral negotiation handling, in a homogeneous setting, both numerical features and non-numerical ones. The framework makes possible to formally represent typical situations in real e-marketplaces such as “if I spend more than 20000 € for a sedan then I want a navigator pack included” where both numerical (price) and non-numerical (sedan, navigator pack) issues coexist. To this aim we introduce \(\mathcal{P}(\mathcal{N})\), a propositional logic extended with concrete domains, which allows to: model relations among issues (both numerical and not numerical ones) via logical entailment, differently from well-known approaches that describe issues as uncorrelated; represent buyer’s request, seller’s supply and their respective preferences as formulas endowed with a formal semantics. By modeling preferences as formulas it is hence possible to assign a utility value also to a bundle of issues, which is obviously more realistic than the trivial sum of utilities assigned to single elements in the bundle itself. We illustrate the theoretical framework, the logical language, the one-shot negotiation protocol we adopt, and show we are able to compute Pareto-efficient outcomes, using a mediator to solve a multi-objective optimization problem.KeywordsPropositional LogicNegotiation ProcessNumerical FeatureMulti Objective Optimization ProblemStrict RequirementThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.