Abduction for (non-ominiscient) agents

Among the non-monotonic reasoning processes, abduction is one of the most important. Usually described as the process of looking florexplantions, it has been recognized as one of the most commonly used in our daily activities. Still, the traditional definitions of an abductive problem and an abductive solution mention only theories and formulas, leaving agency out of the picture. Our work proposes a study of abductive reasoning from an epistemic and dynamic perspective, making special emphasis on non-ideal agents. We begin by exploring what an abductive problema is in terms of an agent’s information, and what an abductive solution is in terms of the actions that modify it. Then we explore the different kinds of abductive problems and abductive solutions that arise when we consider agents whose information is not closed under logical consequence, and agents whose reasoning abilities are not complete

Analysis of Implicit Uncertain Systems. Part II: Constant Matrix Problems and Application to Robust H2 Analysis

This paper introduces an implicit framework for the analysis of uncertain systems, of which the general properties were described in Part I. In Part II, the theory is specialized to problems which admit a finite dimensional formulation. A constant matrix version of implicit analysis is presented, leading to a generalization of the structured singular value μ as the stability measure; upper bounds are developed and analyzed in detail. An application of this framework results in a practical method for robust H2 analysis: computing robust performance in the presence of norm-bounded perturbations and white-noise disturbances