Program conversing in Portugese providing a library service

TUGA is a program which converses in Portuguese to provide a library service covering the field of Artificial Intelligence. The objective of designing the program TUGA was the development of a feasible method for consulting and creating data bases in natural Portuguese. The resulting program allows dialogues where the program and its users behave in the way humans normally do in a dialogue setting. The program can answer/ and question in pre-defined scenarios. Users can question/ answer and issue commands in a natural and convenient way/ without bothering excessively with the form of the dialogues and sentences. The original contributions of this work are: the treatment of dialogues. the adaptation of Colmerauer's natural language framework to Portuguese, the particular method for evaluating the logical structures involved in Colmerauer's framework, and the library service application itself. The program is implemented in Prolog, a simple and surprisingly powerful programming language essentially identical in syntax and semantics to a subset of predicate calculus in clausal form

Machine learning and its applications in reliability analysis systems

In this thesis, we are interested in exploring some aspects of Machine Learning (ML) and its application in the Reliability Analysis systems (RAs). We begin by investigating some ML paradigms and their- techniques, go on to discuss the possible applications of ML in improving RAs performance, and lastly give guidelines of the architecture of learning RAs. Our survey of ML covers both levels of Neural Network learning and Symbolic learning. In symbolic process learning, five types of learning and their applications are discussed: rote learning, learning from instruction, learning from analogy, learning from examples, and learning from observation and discovery. The Reliability Analysis systems (RAs) presented in this thesis are mainly designed for maintaining plant safety supported by two functions: risk analysis function, i.e., failure mode effect analysis (FMEA) ; and diagnosis function, i.e., real-time fault location (RTFL). Three approaches have been discussed in creating the RAs. According to the result of our survey, we suggest currently the best design of RAs is to embed model-based RAs, i.e., MORA (as software) in a neural network based computer system (as hardware). However, there are still some improvement which can be made through the applications of Machine Learning. By implanting the 'learning element', the MORA will become learning MORA (La MORA) system, a learning Reliability Analysis system with the power of automatic knowledge acquisition and inconsistency checking, and more. To conclude our thesis, we propose an architecture of La MORA

Intelligence Without Reason

Computers and Thought are the two categories that together define Artificial Intelligence as a discipline. It is generally accepted that work in Artificial Intelligence over the last thirty years has had a strong influence on aspects of computer architectures. In this paper we also make the converse claim; that the state of computer architecture has been a strong influence on our models of thought. The Von Neumann model of computation has lead Artificial Intelligence in particular directions. Intelligence in biological systems is completely different. Recent work in behavior-based Artificial Intelligenge has produced new models of intelligence that are much closer in spirit to biological systems. The non-Von Neumann computational models they use share many characteristics with biological computation

Artificially Intelligent Copyright: Rethinking Copyright Boundaries

My dissertation explores the legal boundaries of copyright law in the wake of artificial intelligence (AI) technology. In building the theoretical foundations for my dissertation, I go through several key phases. First, I highlight important historical events and milestones in AI. I further develop the philosophical debate on AI legal personhood and deliberate whether we are approaching a singularity the next stage of AI evolution. I also explore the concept of AI as it matured through the years. In the second part, I theorize how AI can be regarded as an author under IP normative standards. Part of accepting the argument that AI deserve copyright is a willingness to change the perception that only human creations are worthy of copyright protection. I also seek an answer to two sub-questions the who and the what. The who considers the normative standards of authorship in the ongoing struggle between an authors right and the public domain. The what raise the originality debate and discusses the standard of creation. In the third part, I outline the many candidates for AI authorship the programmer, the user, the AI and an alternative legal framework for AIs ownership like the public domain or author-in-law. Finally, I discuss the outcomes of each model and provide my conclusions

Intelligence, from Natural Origins to Artificial Frontiers - Human Intelligence vs. Artificial Intelligence

The parallel history of the evolution of human intelligence and artificial intelligence is a fascinating journey, highlighting the distinct but interconnected paths of biological evolution and technological innovation. This history can be seen as a series of interconnected developments, each advance in human intelligence paving the way for the next leap in artificial intelligence. Human intelligence and artificial intelligence have long been intertwined, evolving in parallel trajectories throughout history. As humans have sought to understand and reproduce intelligence, AI has emerged as a field dedicated to creating systems capable of tasks that traditionally require human intellect. This book examines the evolutionary roots of intelligence, explores the emergence of artificial intelligence, examines the parallel history of human intelligence and artificial intelligence, tracing their development, interactions, and profound impact they have had on each other, and envisions future landscapes where intelligence converges human and artificial. Let's explore this history, comparing key milestones and developments in both realms

L'intelligence, des origines naturelles aux frontières artificielles - Intelligence humaine vs. Intelligence artificielle

L’histoire parallèle de l’évolution de l’intelligence humaine et de l’intelligence artificielle constitue un voyage fascinant, mettant en lumière les voies distinctes mais interconnectées de l’évolution biologique et de l’innovation technologique. Cette histoire peut être considérée comme une série de développements interconnectés, chaque avancée de l’intelligence humaine ouvrant la voie au prochain bond en avant de l’intelligence artificielle. L’intelligence humaine et l’intelligence artificielle sont depuis longtemps liées, évoluant selon des trajectoires parallèles tout au long de l’histoire. Alors que les humains cherchent à comprendre et à reproduire l’intelligence, l’IA est devenue un domaine dédié à la création de systèmes capables d’accomplir des tâches qui nécessitent traditionnellement l’intellect humain. Ce livre examine les racines évolutives de l'intelligence, explore l'émergence de l'intelligence artificielle, examine l'histoire parallèle de l'intelligence humaine et de l'intelligence artificielle, retraçant leur développement, leurs interactions et l'impact profond qu'elles ont eu les unes sur les autres, et envisage les paysages futurs où l'intelligence humaine et artificielle converge. Explorons cette histoire, en comparant les étapes clés et les développements dans les deux domaines

Inventing Intelligence: On the History of Complex Information Processing and Artificial Intelligence in the United States in the Mid-Twentieth Century

In the mid-1950s, researchers in the United States melded formal theories of problem solving and intelligence with another powerful new tool for control: the electronic digital computer. Several branches of western mathematical science emerged from this nexus, including computer science (1960s–), data science (1990s–) and artificial intelligence (AI). This thesis offers an account of the origins and politics of AI in the mid-twentieth century United States, which focuses on its imbrications in systems of societal control. In an effort to denaturalize the power relations upon which the field came into being, I situate AI’s canonical origin story in relation to the structural and intellectual priorities of the U.S. military and American industry during the Cold War, circa 1952 to 1961. This thesis offers a detailed and comparative account of the early careers, research interests, and key outputs of four researchers often credited with laying the foundations for AI and machine learning—Herbert A. Simon, Frank Rosenblatt, John McCarthy and Marvin Minsky. It chronicles the distinct ways in which each sought to formalise and simulate human mental behaviour using digital electronic computers. Rather than assess their contributions as discontinuous with what came before, as in mythologies of AI's genesis, I establish continuities with, and borrowings from, management science and operations research (Simon), Hayekian economics and instrumentalist statistics (Rosenblatt), automatic coding techniques and pedagogy (McCarthy), and cybernetics (Minsky), along with the broadscale mobilization of Cold War-era civilian-led military science generally. I assess how Minsky’s 1961 paper 'Steps Toward Artificial Intelligence' simultaneously consolidated and obscured these entanglements as it set in motion an initial research agenda for AI in the following two decades. I argue that mind-computer metaphors, and research in complex information processing generally, played an important role in normalizing the small- and large-scale structuring of social behaviour using mathematics in the United States from the second half of the twentieth century onward

Machine intelligence and robotics: Report of the NASA study group

Opportunities for the application of machine intelligence and robotics in NASA missions and systems were identified. The benefits of successful adoption of machine intelligence and robotics techniques were estimated and forecasts were prepared to show their growth potential. Program options for research, advanced development, and implementation of machine intelligence and robot technology for use in program planning are presented

Inteligența, de la originile naturale la frontierele artificiale - Inteligența Umană vs. Inteligența Artificială

Istoria paralelă a evoluției inteligenței umane și a inteligenței artificiale este o călătorie fascinantă, evidențiind căile distincte, dar interconectate, ale evoluției biologice și inovației tehnologice. Această istorie poate fi văzută ca o serie de evoluții interconectate, fiecare progres în inteligența umană deschizând calea pentru următorul salt în inteligența artificială. Inteligența umană și inteligența artificială s-au împletit de mult timp, evoluând în traiectorii paralele de-a lungul istoriei. Pe măsură ce oamenii au căutat să înțeleagă și să reproducă inteligența, IA a apărut ca un domeniu dedicat creării de sisteme capabile de sarcini care necesită în mod tradițional intelect uman. Această carte analizează rădăcinile evolutive ale inteligenței, explorează apariția inteligenței artificiale, analizează istoria paralelă a inteligenței umane și a inteligenței artificiale, urmărind dezvoltarea lor, interacțiunile și impactul profund pe care l-au avut una asupra celeilalte, și imaginează peisajele viitoare în care converg inteligența umană și cea artificială. Să explorăm această istorie, comparând reperele cheie și evoluțiile din ambele tărâmuri

Basic characteristics to achieve common sense reasoning

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