An Adaptive Logic Based on Jaśkowskiˈs Approach to Paraconsistency

نویسنده

  • Joke Meheus
چکیده

Discussive logics (also called discursive logics) were introduced in 1948 by Stanis law Jaśkowski and constitute the first family of formal paraconsistent logics. The basic mechanism behind discussive logics is as simple as ingenious. Where L is some modal logic and Γ♦ = {♦A | A ∈ Γ}, a discussive logic DL, associated with L, is obtained by specifying the language L of DL and by stipulating that, where A and the members of Γ are well-formed formulas of L, Γ `DL A iff Γ♦ `L ♦A. It is easily observed that, given an appropriate choice of L and of L, DL is paraconsistent. This is the case, for instance, if L is the language of Classical Logic (henceforth CL) and L is S5 (in view of ♦A, ♦∼A 0S5 ♦B). Where “∧” stands for the classical conjunction, discussive logics moreover do not allow to infer A ∧ ∼A from A and ∼A (in view of ♦A, ♦∼A 0L ♦(A ∧ ∼A)). Especially from the perspective of interpreting discussions, discussive logics seem highly attractive. If two participants in a discussion contradict each other, we tend to interpret their statements in a modal way: “Someone accepts A; someone accepts ∼A”. From this, neither “someone accepts B” nor “someone accepts both A and ∼A” follows. This is exactly what discussive logics allow for. There is, however, a drawback. If L comprises the classical connectives, the above mechanism leads to a system that is as rich as CL for single-premise inferences, but that invalidates all interesting multiple-premise inferences of CL (Adjunction, Modus Ponens, Modus Tollens, . . . ). This is why Jaśkowski dismissed the idea to formulate discussive logics in terms of the classical connectives (see [17, pp. 149–150]). Instead, he proposed

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Designing an adaptive fuzzy control for robot manipulators using PSO

This paper presents designing an optimal adaptive controller for tracking control of robot manipulators based on particle swarm optimization (PSO) algorithm. PSO algorithm has been employed to optimize parameters of the controller and hence to minimize the integral square of errors (ISE) as a performance criteria. In this paper, an improved PSO using logic is proposed to increase the convergenc...

متن کامل

Design of Fuzzy Logic Based PI Controller for DFIG-based Wind Farm Aimed at Automatic Generation Control in an Interconnected Two Area Power System

This paper addresses the design procedure of a fuzzy logic-based adaptive approach for DFIGs to enhance automatic generation control (AGC) capabilities and provide better dynamic responses in multi-area power systems. In doing so, a proportional-integral (PI) controller is employed in DFIG structure to control the governor speed of wind turbine. At the first stage, the adjustable parameters of ...

متن کامل

IS-MRAS With On-Line Adaptation Parameters Based on Type-2 Fuzzy LOGIC for Sensorless Control of IM

This paper suggests novel sensorless speed estimation for an induction motor (IM) based on a stator current model reference adaptive system (IS-MRAS) scheme. The IS-MRAS scheme uses the error between the reference and estimated stator current vectors and the rotor speed. Observing rotor flux and the speed estimating using the conventional MRAS technique is confronted with certain problems relat...

متن کامل

Indirect Adaptive Interval Type-2 Fuzzy PI Sliding Mode Control for a Class of Uncertain Nonlinear Systems

Controller design remains an elusive and challenging problem foruncertain nonlinear dynamics. Interval type-2 fuzzy logic systems (IT2FLS) incomparison with type-1 fuzzy logic systems claim to effectively handle systemuncertainties especially in the presence of disturbances and noises, but lack aformal mechanism to guarantee performance. In contrast, adaptive sliding modecontrol (ASMC) provides...

متن کامل

ADAPTIVE FUZZY TRACKING CONTROL FOR A CLASS OF PERTURBED NONLINEARLY PARAMETERIZED SYSTEMS USING MINIMAL LEARNING PARAMETERS ALGORITHM

In this paper, an adaptive fuzzy tracking control approach is proposed for a class of single-inputsingle-output (SISO) nonlinear systems in which the unknown continuous functions may be nonlinearlyparameterized. During the controller design procedure, the fuzzy logic systems (FLS) in Mamdani type are applied to approximate the unknown continuous functions, and then, based on the minimal learnin...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • J. Philosophical Logic

دوره 35  شماره 

صفحات  -

تاریخ انتشار 2006