The Problem of Mental Action

In mental action there is no motor output to be controlled and no sensory input vector that could be manipulated by bodily movement. It is therefore unclear whether this specific target phenomenon can be accommodated under the predictive processing framework at all, or if the concept of “active inference” can be adapted to this highly relevant explanatory domain. This contribution puts the phenomenon of mental action into explicit focus by introducing a set of novel conceptual instruments and developing a first positive model, concentrating on epistemic mental actions and epistemic self-control. Action initiation is a functionally adequate form of self-deception; mental actions are a specific form of predictive control of effective connectivity, accompanied and possibly even functionally mediated by a conscious “epistemic agent model”. The overall process is aimed at increasing the epistemic value of pre-existing states in the conscious self-model, without causally looping through sensory sheets or using the non-neural body as an instrument for active inference

Argumentation and data-oriented belief revision: On the two-sided nature of epistemic change

This paper aims to bring together two separate threads in the formal study of epistemic change: belief revision and argumentation theories. Belief revision describes the way in which an agent is supposed to change his own mind, while argumentation deals with persuasive strategies employed to change the mind of other agents. Belief change and argumentation are two sides (cognitive and social) of the same epistemic coin. Argumentation theories are therefore incomplete, if they cannot be grounded in belief revision models - and vice versa. Nonetheless, so far the formal treatment of belief revision widely neglected any systematic comparison with argumentation theories. Such lack of integration poses severe limitations to our understanding of epistemic change, and more comprehensive models should instead be devised. After a short critical review of the literature (cf. 1), we outline an alternative model of belief revision whose main claim is the distinction between data and beliefs (cf. 2), and we discuss in detail its expressivity with respect to argumentation (cf. 3): finally, we summarize our conclusions and future works on the interface between belief revision and argumentation (cf. 4)

A Reasoning System for a First-Order Logic of Limited Belief

Logics of limited belief aim at enabling computationally feasible reasoning in highly expressive representation languages. These languages are often dialects of first-order logic with a weaker form of logical entailment that keeps reasoning decidable or even tractable. While a number of such logics have been proposed in the past, they tend to remain for theoretical analysis only and their practical relevance is very limited. In this paper, we aim to go beyond the theory. Building on earlier work by Liu, Lakemeyer, and Levesque, we develop a logic of limited belief that is highly expressive while remaining decidable in the first-order and tractable in the propositional case and exhibits some characteristics that make it attractive for an implementation. We introduce a reasoning system that employs this logic as representation language and present experimental results that showcase the benefit of limited belief.Comment: 22 pages, 0 figures, Twenty-sixth International Joint Conference on Artificial Intelligence (IJCAI-17

Weighted logics for artificial intelligence : an introductory discussion

International audienceBefore presenting the contents of the special issue, we propose a structured introductory overview of a landscape of the weighted logics (in a general sense) that can be found in the Artificial Intelligence literature, highlighting their fundamental differences and their application areas

Other uncertainty theories based on capacities

International audienceThe two main uncertainty representations in the literature that tolerate imprecision are possibility distributions and random disjunctive sets. This chapter devotes special attention to the theories that have emerged from them. The first part of the chapter discusses epistemic logic and derives the need for capturing imprecision in information representations. It bridges the gap between uncertainty theories and epistemic logic showing that imprecise probabilities subsume modalities of possibility and necessity as much as probability. The second part presents possibility and evidence theories, their origins, assumptions and semantics, discusses the connections between them and the general framework of imprecise probability. Finally, chapter points out the remaining discrepancies between the different theories regarding various basic notions, such as conditioning, independence or information fusion and the existing bridges between them

Creationism and evolution

In Tower of Babel, Robert Pennock wrote that “defenders of evolution would help their case immeasurably if they would reassure their audience that morality, purpose, and meaning are not lost by accepting the truth of evolution.” We first consider the thesis that the creationists’ movement exploits moral concerns to spread its ideas against the theory of evolution. We analyze their arguments and possible reasons why they are easily accepted. Creationists usually employ two contradictive strategies to expose the purported moral degradation that comes with accepting the theory of evolution. On the one hand they claim that evolutionary theory is immoral. On the other hand creationists think of evolutionary theory as amoral. Both objections come naturally in a monotheistic view. But we can find similar conclusions about the supposed moral aspects of evolution in non-religiously inspired discussions. Meanwhile, the creationism-evolution debate mainly focuses — understandably — on what constitutes good science. We consider the need for moral reassurance and analyze reassuring arguments from philosophers. Philosophers may stress that science does not prescribe and is therefore not immoral, but this reaction opens the door for the objection of amorality that evolution — as a naturalistic world view at least — supposedly endorses. We consider that the topic of morality and its relation to the acceptance of evolution may need more empirical research

Logic-based Technologies for Intelligent Systems: State of the Art and Perspectives

Together with the disruptive development of modern sub-symbolic approaches to artificial intelligence (AI), symbolic approaches to classical AI are re-gaining momentum, as more and more researchers exploit their potential to make AI more comprehensible, explainable, and therefore trustworthy. Since logic-based approaches lay at the core of symbolic AI, summarizing their state of the art is of paramount importance now more than ever, in order to identify trends, benefits, key features, gaps, and limitations of the techniques proposed so far, as well as to identify promising research perspectives. Along this line, this paper provides an overview of logic-based approaches and technologies by sketching their evolution and pointing out their main application areas. Future perspectives for exploitation of logic-based technologies are discussed as well, in order to identify those research fields that deserve more attention, considering the areas that already exploit logic-based approaches as well as those that are more likely to adopt logic-based approaches in the future

Leadership in Research : Transformational Leadership and Commitment to Concepts in Knowledge Creation

While the autonomy of research professionals isconsidered a crucial condition for the quality oftheir findings, leadership of research is also seennecessary for the efficiency and quality ofresearch work in research teams. Leadership maybe effective in terms of knowledge creation, butthis area is poorly understood. This articleanalyses the nature of commitment to conceptsas part of the effect of transformationalleadership on research work within a group. Theconclusion is that leadership is an integral part ofknowledge creation, not just of knowledgesharing and exploitation. Effective leadershipresults in the mixture of epistemic and socialcommitments that makes a group a collectiveknower, not just a sum of individual knowers.The analysis of conceptual commitmentscontributes to understanding the rejectionist/believer debate of social epistemology in a newlight