Ecological Rationality and Evolutionary Medicine:

This paper considers the possibility of designing AI that can learn logical or non-logical inference rules from data. We first provide an abstract framework for learning logics. In this framework, an agent $${{{\mathcal {A}}}}$$ provides training examples that consist of formulas S and their logical consequences T. Then a machine $${{{\mathcal {M}}}}$$ builds an axiomatic system that makes T a consequence of S. Alternatively, in the absence of an agent $$\mathcal{A}$$ , a machine $${{{\mathcal {M}}}}$$ seeks an unknown logic underlying given data. We next consider the problem of learning logical inference rules by induction. Given a set S of propositional formulas and their logical consequences T, the goal is to find deductive inference rules that produce T from S. We show that an induction algorithm LF1T, which learns logic programs from interpretation transitions, successfully produces deductive inference rules from input data. Finally, we consider the problem of learning non-logical inference rules. We address three case studies for learning abductive inference, frame axioms, and conversational implicature. Each case study uses machine learning techniques together with metalogic programming.

The notion of ecological rationality sees human rationality as the result of the adaptive fit between the human mind and the environment. Ecological rationality focuses the study of decision making on two key questions: First, what are the environmental regularities to which people’s decision strategies are matched, and how frequently do these regularities occur in natural environments? Second, how well can people adapt their use of specific strategies to particular environmental regularities? Research on aging suggests a number of changes in cognitive function, for instance, deficits in learning and memory that may impact decision-making skills. However, it has been shown that simple strategies can work well in many natural environments, which suggests that age-related deficits in strategy use may not necessarily translate into reduced decision quality. Consequently, we argue that predictions about the impact of aging on decision performance depend not only on how aging affects decision-relevant capacities but also on the decision environment in which decisions are made. In sum, we propose that the concept of the ecological rationality is crucial to understanding and aiding the aging decision maker.

Sequent calculi for applied logics have nonstandard logical inference rules and various axioms, cut is essential in them. The following constraints on derivations in these calculi do not compromise completeness. Contraction rules follow cut and logical rules. Weakening rules precede logical rules. Consecutive cut rules are ordered so that larger formulas are cut first. Consecutive standard logical rules are ordered so that their principal formulas are in an increasing order.

Actual scientific researches and issues analysis. Research on large language models (LLM) compliance with the rules of formal logic has been conducted by various groups of scientists led by R. Nishant, J. Wan, M. Amirizani, T. Liu, and H. Chi. The work of S. Wang demonstrates that AI's mastery of the fundamental rules of inference still falls short of human capabilities and suggests approaches for testing and enhancing AI's logical skills. E. Larson shows why artificial intelligence cannot understand texts; however, he does not specifically investigate artificial intelligence's adherence to the rules of formal logic. B. Lin explores the use of mathematical methods to improve artificial intelligence accuracy. Research indicates that artificial intelligence can be trained to follow the rules of formal logic, but this process may require significant effort and resources. The research objective. The task of this article is to test the artificial intelligence service at https://deepai.org/chat for its ability to adhere to the rules of formal logic, specifically solving problems related to modus ponens and modus tollens. Understanding this aspect will allow for a better understanding of the capabilities of language-based artificial intelligence and assist users in obtaining more accurate results. The statement of basic materials. The article is dedicated to analyzing logical inferences, particularly the rules of modus ponens and modus tollens in the context of interaction with artificial intelligence (AI). Two examples are examined. In the first case, from two premises (“If it is raining outside, then the pavement is wet” and “The pavement outside is wet”), artificial intelligence makes an incorrect conclusion, asserting that “it is raining outside,” despite this being an incorrect application of modus ponens. The authors emphasize that common sense indicates that the pavement could be wet for other reasons. In the second example, concerning modus tollens, artificial intelligence reaches yet another incorrect conclusion. Again, it is noted that a correct conclusion can only be drawn from proper logical thinking schemes. Although artificial intelligence has succeeded in some logical tasks, the author considers this a coincidence rather than confirmation of logical thinking ability. Testing for errors in conclusions shows that even when artificial intelligence formulates conclusions incorrectly, it can indicate the need for additional information to make a correct inference. Thus, the article highlights the limitations of contemporary artificial intelligence models in understanding logic and underscores the necessity for critical thinking on the part of users when interacting with them.

Ensuring constant synchronicity between the IT Architecture (ITA) and the actual Information Systems (IS) without the help of automatic tools is an intractable task, especially when taking into account modern IS' rapid evolution and growing complexity and distributed nature. We propose an automatic AS-IS ITA verification methodology and framework based on deep passive network traffic analysis and logical inference rules with the goal of inferring relevant facts about the actual ITA. The resulting knowledge is described according to a conceptual model designed for this purpose. We also propose an organization-independent mapping relationship between that ITA network evidence model and an ISA modeling framework (CEO Framework), at the technology (ITA) level, realized through a set of logical deduction rules. These rules formally define the conditions that must hold between the inferred evidence and a high-level ITA model (both represented in this inference system) in order to declare that model factual and in line with reality. It is the automatic execution of these rules that realizes the verification process that reports, as a result, all the significant detected discrepancies. The proposed concepts and methodology are implemented in a prototype applied to a case study in the leading Portuguese Telecom operator. The proposed solution was shown to be capable of successfully verifying the case study's ITA model as well as discovering new, undocumented, information through logical inference.

Sendai Framework for Disaster Risk Reduction 2015-2030 highlights education, public awareness, and knowledge sharing as key priorities for strengthening disaster risk governance and building resilient societies (UNDRR). In this context, effective disaster risk reduction requires not only advances in scientific knowledge, but also sustained science-society interaction, inclusive risk communication, and long-term engagement strategies.For about 20 years, the LARES Association - Italian Union of Civil Protection Experts, has been actively committed to promoting a culture of prevention and safety, bridging scientific expertise, civil protection institutions, volunteers, and citizens. LARES operates with the aim of translating scientific knowledge on natural hazards into accessible information and practical behaviours, in line with the Sendai Framework’s emphasis on education and capacity building.LARES adopts a multidisciplinary and participatory approach, focusing on the co-production of knowledge and on educational pathways tailored to different audiences: students, educators, volunteers, professionals, and the general public. Its activities combine formal and informal education, experiential learning, and innovative communication tools to enhance risk awareness, preparedness, and individual and collective responsibility.A cornerstone of LARES’s educational outreach is “SicuraMente Lab”, an interactive programme designed for secondary schools and universities, which has trained around 10,000 students, involving more than 70 schools and approximately 100 volunteer trainers. The project integrates workshops, hands-on activities, web platform, and expert contributions to introduce civil protection principles, multi-hazard scenarios (earthquakes, floods, landslides, and fires), and self-protection measures, fostering critical thinking and risk literacy among younger generations.LARES also plays an active role in “Io non Rischio”, the national awareness campaign coordinated by the Italian Civil Protection Department. Through engagement in public spaces and digital formats, trained volunteers disseminate scientifically validated information on natural hazards and preparedness practices, promoting dialogue, trust-building, and shared responsibility between institutions and communities. To date, dozens of events have been organized in 9 regions, reaching thousands of people.Public engagement is further strengthened through “Terremoti d’Italia”, an itinerant exhibition combining scientific content, historical memory, and interactive communication to explain seismic processes and promote preventive actions. Since 2007, around 30 editions have been organized in Italy and abroad with the participation of LARES volunteers.Innovation in risk communication is a key element of LARES’s strategy. The “Sisma VR” project, a virtual reality earthquake simulation, immerses users in realistic scenarios to enhance understanding of seismic risk and appropriate response behaviours through the use of commercial VR headsets.In addition, the popular videogame “Minecraft” has been exploited to develop a flood risk scenario in urban area using familiar digital environments to engage younger audiences, encouraging preparedness through play and simulation. The Minecraft-based scenario will soon be published on the Minecraft Education platform, making it available to teachers and educators worldwide.Together, these initiatives demonstrate how education-oriented, science-based communication and stakeholder engagement can effectively support the diffusion of prevention and safety culture. The LARES experience provides transferable practices aligned with the Sendai Framework priorities, contributing to informed, aware, and resilient communities.

This chapter presents a survey aimed at identifying the level of usability and applicability of interoperable educational tools in Nigeria language teacher education. The background summarizes the benefits of e-technologies in learning process. It then explores the different types of interoperable tools and e-competencies required by pre-service teachers in a second language context. Utilising one Nigerian University as a case study, the survey sampled one hundred teacher trainees selected from 300 level English Education students’ of the Department of Arts and Social Science Education, University of Lagos, Nigeria. Two research questions were posited while two instruments- the Internet Application Competence Assignment (IACA) and the Internet Literacy Competency Questionnaire (ILCQ) were used in data sourcing. Analysis of data involved descriptive and inferential statistics. On the whole, findings show that 39% of the pre-service teachers operated within low level Internet skills, 49% were able to operate within higher competency level while the consolidated level skills posed the most difficult area of competency in usability of interoperable educational tools in language teacher education. The chapter ends with proposed solutions and recommendations for futuristic research directions within the context of global e-learning support.

The paper proposes a method for semantic message matching in automatic service composition. It develops a framework in which the exported message description and behavior description of a service, and represents the behavior of a service with a finite state machine. Since the service interface definition can be represented by ontology concepts, the internal representation language enables us to define some issues required by service composition formally, qualitative and quantitative constraints plus reasoning on concepts, and the service behavior can be represented using linear logic formulas, so the inference rules of linear logic can check the match-ability and satisfy-ability of service message.

We explore the consequences, for logical system-building, of taking seriously (i) the aim of having irredundant rules of inference, and (ii) a preference for proofs of stronger results over proofs of weaker ones. This leads one to reconsider the structural rules of REFLEXIVITY, THINNING, and CUT. REFLEXIVITY survives in the minimally necessary form φ:φ. Proofs have to get started. CUT is subject to a CUT-elimination theorem, to the effect that one can always make do without applications of CUT. So CUT is redundant, and should not be a rule of the system. CUT-elimination, however, in the context of the usual forms of logical rules, requires the presence, in the system, of THINNING. But THINNING, it turns out, is not really necessary. Provided only that one liberalizes the statement of certain logical rules in an appropriate way, one can make do without CUT or THINNING. From the methodological point of view of this study, the logical rules ought to be framed in this newly liberalized form. These liberalized logical rules determine the system of core logic. Given any intuitionistic Gentzen proof of Δ:φ, one can determine from it a Core proof of some subsequent of Δ:φ. Given any classical Gentzen proof of Δ:φ, one can determine from it a classical Core proof of some subsequent of Δ:φ. In both cases the Core proof is of a result at least as strong as that of the Gentzen proof; and the only structural rule used is φ:φ.

We study unification of formulas in multi-modal LTK logic and give a syntactic description of all formulas which are non-unificable in this logic. Passive inference rules are considered, it is shown that in LTK logic there is a finite basis for passive rules.

We present a general storage model that reflects features of object oriented (OO) languages with pure reference semantics. Based on this model, we develop an OO Separation Logic (OOSL) to specify and verify OO programs. Many inference rules in the Separation Logic still hold in OOSL. Additionally, OOSL has certain properties important to OO reasoning. We introduce Hoare-Triple for a small OO language, and use the Schorr-Waite Marking Algorithm as a verification example.

The main result of this paper is a complete semantics description of all modal logics with finite model property that preserves all admissible for S4 inference rules: a modal logic λ with fmp above S4 preserves the admissibility iff λ has so-called co-cover property. As an application it is shown that there are continuously many logics of this kind. On base mentioned above semantical criterion, as corollary, we give some precise description of all tabular logics that preserves admissible for S4 rules.

A. History, according to Aristotle, is an account of what individual human beings have done and suffered. More widely still, history is what historians do. Is history, in this sense, a science, as, let us say, physics or biology or psychology are sciences? And if not, should it seek to be one? And if it fails to be one, what prevents it? Is this due to human weakness, or to the nature of the subject, or does the very problem rest on a confusion between the concept of history and that of natural science? These have been questions that have occupied the minds of both philosophers and philosophically minded historians at least since the beginning of the nineteenth century, when men became self-conscious about the purpose and logic of their intellectual activities. But two centuries before that, Descartes had already denied to history any claim to be a serious study. Those who accepted the validity of the Cartesian criterion of what constitutes rational method could (and did) ask how they could find the clear and simple elements of which historical judgments were composed, and into which they could be analysed; where were the definitions, the logical transformation rules, the rules of inference, the rigorously deduced conclusions? While this confused amalgam of memories and travelers' tales, fables and chroniclers' stories, moral reflections and gossip, might be a harmless pastime, it was beneath the dignity of serious men seeking what alone is worth seeking the discovery of the truth in accordance with the principles and rules which alone guarantee scientific validity. Ever since this doctrine of what was and what was not a science was enunciated, those who have thought about the nature of historical studies have laboured under the stigma of the Cartesian condemnation. Some have tried to show that history could be made respectable by being assimilated to one of the natural sciences, whose overwhelming success and prestige in the seventeenth and eighteenth centuries held out promise of rich fruit wherever their methods were applicable; others declared that history was indeed a science, but a science in some different sense, with its own methods and canons, no less exacting than those of the sciences of nature, but resting on foundations different from them; others defiantly declared that history was indeed subjective, impressionistic, incapable of being made rigorous, a branch of literature, or an expression

Background: Globally, stomach cancer remains a considerable health burden, largely due to insufficient public understanding of its risk factors and preventive strategies. Educating future educators, such as B.Ed. students, can significantly enhance community-level health literacy.Objectives: The study aimed to (1) To determine the existing knowledge of B.Ed. students regarding stomach cancer risk factors and prevention, (2) To evaluate the impact of a self-instructional module (SIM), and (3) To assess the correlation between post-test knowledge and specific socio-demographic variables.Methods: A pre-experimental one-group pre-test and post-test approach was utilized with 50 purposively chosen B.Ed. students from a college in Dharwad. A validated structured questionnaire was administered before and one week after providing the SIM. Data analysis employed both descriptive and inferential statistics, including paired t-tests and chi-square tests.Results: A statistically significant improvement was noted in the knowledge scores post-intervention (p< 0.05). Significant relationships were found between knowledge gains and variables like age, gender, familial stomach cancer history, and primary source of health information.Conclusion: The SIM effectively enhanced B.Ed. students' understanding of stomach cancer and its prevention. Incorporating such educational tools into academic curricula can contribute to widespread health awareness.

The integration of assistive technology and accessibility tools is transforming education for students with disabilities. This chapter examines the development, significance, and future potential of these technologies within adaptive education frameworks. It analyzes tools such as wearable technology, virtual and augmented reality, artificial intelligence, and universal design, highlighting their role in fostering independent learning and personal growth. The discussion includes successful implementation strategies and case studies that demonstrate how assistive technology enhances self-advocacy and participation. Additionally, it addresses challenges, financial, logistical, and attitudinal that hinder adoption, along with proposed solutions. The chapter emphasizes the need for inclusive policies and partnerships to create a sustainable ecosystem for assistive technology deployment, ensuring equitable access to learning materials for all students as these tools evolve.