Integración de modelos de razonamiento práctico, tecnologías de acuerdo y aprendizaje

Este artículo describe, en forma breve, los trabajos de investigación y desarrollo que se están llevando a cabo en la línea de investigación “Agentes Inteligentes” en la problemática vinculada a la integración de tecnologías de acuerdo y aprendizaje dentro de arquitecturas de razonamiento práctico. Se abordan temas vinculados a arquitecturas de agentes inteligentes (en particular, arquitecturas BDI y Procesos de Decisión Markov), mecanismos de votación, argumentación y negociación como tecnologías de acuerdo, y aprendizaje automático.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

Tecnologías de acuerdo en modelos de razonamiento práctico

En este artículo se describen, en forma resumida, los trabajos de investigación y desarrollo que se están llevando a cabo en la línea de investigación “Sistemas Inteligentes” en la problemática vinculada a la integración de tecnologías de acuerdo dentro de arquitecturas de razonamiento práctico, y se abordan temas vinculados a arquitecturas de agentes inteligentes, arquitecturas BDI y Procesos de Decisión Markov, mecanismos de votación, argumentación y negociación.Eje: Agentes y sistemas inteligentesRed de Universidades con Carreras en Informática (RedUNCI

Strategic Executions of Choreographed Timed Normative Multi-Agent Systems

This paper proposes a combined mechanism for coordinating agents in timed normative multi-agent systems. Timing constraints in a multi-agent system make it possible to force action execution to happen before certain time invariants are violated. In such multiagent systems we achieve coordination at two orthogonal levels with respect to states and actions. On the one hand, the behaviour of individual agents is regulated by means of social and organisational inspired concepts like norms and sanctions. On the other hand, the behaviour of sets of agents is restricted according to action-based coordination mechanisms called choreographies. In both cases, the resulting behaviour is constrained by time

Refinement Modal Logic

In this paper we present {\em refinement modal logic}. A refinement is like a bisimulation, except that from the three relational requirements only `atoms' and `back' need to be satisfied. Our logic contains a new operator 'all' in addition to the standard modalities 'box' for each agent. The operator 'all' acts as a quantifier over the set of all refinements of a given model. As a variation on a bisimulation quantifier, this refinement operator or refinement quantifier 'all' can be seen as quantifying over a variable not occurring in the formula bound by it. The logic combines the simplicity of multi-agent modal logic with some powers of monadic second-order quantification. We present a sound and complete axiomatization of multi-agent refinement modal logic. We also present an extension of the logic to the modal mu-calculus, and an axiomatization for the single-agent version of this logic. Examples and applications are also discussed: to software verification and design (the set of agents can also be seen as a set of actions), and to dynamic epistemic logic. We further give detailed results on the complexity of satisfiability, and on succinctness