International Journal of Reasoning-based Intelligent Systems 

About: International Journal of Reasoning-based Intelligent Systems is an academic journal published by Inderscience Publishers. The journal publishes majorly in the area(s): Computer science & Pattern recognition (psychology). It has an ISSN identifier of 1755-0556. Over the lifetime, 361 publications have been published receiving 1019 citations.

Modelling morality with prospective logic

Abstract: This paper shows how moral decisions can be drawn computationally by using prospective logic programs. These are employed to model moral dilemmas, as they are able to prospectively look ahead at the consequences of hypothetical moral judgments. With this knowledge of consequences, moral rules are then used to decide the appropriate moral judgments. The whole moral reasoning is achieved via a priori constraints and a posteriori preferences on abductive stable models, two features available in prospective logic programming. In this work, we model various moral dilemmas taken from the classic trolley problem and employ the principle of double effect as the moral rule. Our experiments show that preferred moral decisions, i.e., those following the principle of double effect, are successfully delivered. Additionally, we consider another moral principle, the principle of triple effect, in our implementation. We show that our prospective logic programs allow us to explain computationally different moral judgments...

A new approach to soft sets, soft multisets and their properties

Abstract: Soft set theory is a new mathematical approach to vagueness introduced by Molodtsov (1999). This is a parameterised family of subsets defined over a universal set using a set of parameters. In this paper, we introduce the notion of characteristic function of a soft set, which helps us in defining the basic operations on soft sets concisely; several concepts associated with it efficiently and make the proofs of properties more elegant. We rectified the definition of complement of a soft set and the earlier definition of complement is now called as the negation of a multiset. Like the crisp multisets, soft multiset is a notion which allows multiple occurrences of elements in a model. So far, more than one attempt has been made to define this concept. Out of these the one put forth by Majumdar (2012) is the most appropriate one and so we use it in this paper. We redefined the concepts of complement of a soft multiset, null soft multiset and absolute soft multiset and introduced many operations on soft multisets like the union and intersection of soft multisets and cardinality of soft multisets. Also, we defined the concepts of addition and deletion of elements from a soft multiset. Two new operations, called the addition and difference of two soft multisets are introduced. We establish several properties of these operations on soft multisets including the De Morgan's Law, associative and distributive properties. A real life example is being used for the purpose of illustration of the notions and concepts.

Chaotic time series prediction using Brain Emotional Learning-based Recurrent Fuzzy System (BELRFS)

Abstract: In this paper, an architecture based on the anatomical structure of the emotional network in the brain of mammalians is applied as a prediction model for chaotic time series studies. The architecture is called Brain Emotional Learning-based Recurrent Fuzzy System (BELRFS), which stands for: Brain Emotional Learning-based Recurrent Fuzzy System. It adopts neuro-fuzzy adaptive networks to mimic the functionality of brain emotional learning. In particular, the model is investigated to predict space storms, since the phenomenon has been recognised as a threat to critical infrastructure in modern society. To evaluate the performance of BELRFS, three benchmark time series: Lorenz time series, sunspot number time series and Auroral Electrojet (AE) index. The obtained results of BELRFS are compared with Linear Neuro-Fuzzy (LNF) with the Locally Linear Model Tree algorithm (LoLiMoT). The results indicate that the suggested model outperforms most of data driven models in terms of prediction accuracy.

Bayesian reasoning for Laban Movement Analysis used in human-machine interaction

Abstract: We present the implementation of computational Laban Movement Analysis (LMA) for human-machine interaction using Bayesian reasoning. The research field of computational human movement analysis is lacking a general underlying modelling language, i.e., how to map the features into symbols. With such a semantic descriptor, the recognition problem can be posed as a problem to recognise a sequence of symbols taken from an alphabet consisting of motion-entities. LMA has been proven successful in areas where humans are observing other humans' movements. LMA provides a model for observation and description and a notational system (Labanotation). To implement LMA in a computer, we have chosen a Bayesian approach. The framework allows us to model the process, learn the dependencies between features and symbols and to perform online classification using LMA-labels. We have chosen the application 'social robots' to demonstrate the feasibility of our solution.

Prospective logic agents

Abstract: As we face the actual possibility of modelling agent systems capable of non-deterministic self-evolution, we are confronted with the problem of having several different possible futures for any single agent. This issue brings the challenge of how to allow such evolving agents to be able to look ahead, prospectively, into such hypothetical futures, in order to determine the best courses of evolution from their own present, and thence to prefer amongst them. The concept of prospective logic programs is presented as a way to address such issues. We start by building on previous theoretical background, on evolving programs and on abduction, to construe a framework for prospection and describe an abstract procedure for its materialisation. We take on several examples of modelling prospective logic programs that illustrate the proposed concepts and briefly discuss the ACORDA system, a working implementation of the previously presented procedure. We conclude by elaborating about current limitations of the system...