Academic literature on the topic 'Artificial intelligence. Computer programming'
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Journal articles on the topic "Artificial intelligence. Computer programming"
Lloyd, John W. "Declarative programming for artificial intelligence applications." ACM SIGPLAN Notices 42, no. 9 (2007): 123–24. http://dx.doi.org/10.1145/1291220.1291152.
Full textGini, Maria. "The future of robot programming." Robotica 5, no. 3 (1987): 235–46. http://dx.doi.org/10.1017/s0263574700015897.
Full textXiao, Shu Qiang, and Jian Chun Peng. "The Application of Artificial Intelligence Technology in Electrical Automation Control." Applied Mechanics and Materials 530-531 (February 2014): 1049–52. http://dx.doi.org/10.4028/www.scientific.net/amm.530-531.1049.
Full textZhang, Du, and Michael D. Kramer. "GAPS: A Genetic Programming System." International Journal on Artificial Intelligence Tools 12, no. 02 (2003): 187–206. http://dx.doi.org/10.1142/s0218213003001198.
Full textLian, Fei, and Guang Tian Zou. "Theory and Methods on Tactics Generation of Extension Architectural Programming Facing to Artificial Intelligence." Applied Mechanics and Materials 236-237 (November 2012): 659–65. http://dx.doi.org/10.4028/www.scientific.net/amm.236-237.659.
Full textSokolov, I. A. "Theory and practice in artificial intelligence." Вестник Российской академии наук 89, no. 4 (2019): 365–70. http://dx.doi.org/10.31857/s0869-5873894365-370.
Full textWeng, Juyang. "Autonomous Programming for General Purposes: Theory." International Journal of Humanoid Robotics 17, no. 04 (2020): 2050016. http://dx.doi.org/10.1142/s0219843620500164.
Full textOlson, Eric T. "The Ontological Basis of Strong Artificial Life." Artificial Life 3, no. 1 (1997): 29–39. http://dx.doi.org/10.1162/artl.1997.3.1.29.
Full textShin, Seungki. "A Study on the Framework Design of Artificial Intelligence Thinking for Artificial Intelligence Education." International Journal of Information and Education Technology 11, no. 9 (2021): 392–97. http://dx.doi.org/10.18178/ijiet.2021.11.9.1540.
Full textOLTEAN, MIHAI, CRINA GROŞAN, LAURA DIOŞAN, and CRISTINA MIHĂILĂ. "GENETIC PROGRAMMING WITH LINEAR REPRESENTATION: A SURVEY." International Journal on Artificial Intelligence Tools 18, no. 02 (2009): 197–238. http://dx.doi.org/10.1142/s0218213009000111.
Full textDissertations / Theses on the topic "Artificial intelligence. Computer programming"
Hearn, Robert A. (Robert Aubrey) 1965. "Building grounded abstractions for artificial intelligence programming." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/17510.
Full textIncludes bibliographical references (p. 57-58).
Most Artificial Intelligence (AI) work can be characterized as either "high-level" (e.g., logical, symbolic) or "low-level" (e.g., connectionist, behavior-based robotics). Each approach suffers from particular drawbacks. High-level Al uses abstractions that often have no relation to the way real, biological brains work. Low-level Al, on the other hand, tends to lack the powerful abstractions that are needed to express complex structures and relationships. I have tried to combine the best features of both approaches, by building a set of programming abstractions defined in terms of simple, biologically plausible components. At the "ground level", I define a primitive, perceptron-like computational unit. I then show how more abstract computational units may be implemented in terms of the primitive units, and show the utility of the abstract units in sample networks. The new units make it possible to build networks using concepts such as long-term memories, short-term memories, and frames. As a demonstration of these abstractions, I have implemented a simulator for "creatures" controlled by a network of abstract units. The creatures exist in a simple 2D world, and exhibit behaviors such as catching mobile prey and sorting colored blocks into matching boxes. This program demonstrates that it is possible to build systems that can interact effectively with a dynamic physical environment, yet use symbolic representations to control aspects of their behavior.
by Robert A. Hearn.
S.M.
Sommaruga, Lorenzo. "Cooperative heuristics for autonomous agents : an artificial intelligence perspective." Thesis, University of Nottingham, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.335853.
Full textWerbelow, Wayne Louis. "The application of artificial intelligence techniques to software maintenance." Thesis, Kansas State University, 1985. http://hdl.handle.net/2097/9890.
Full textTout, Kifah Raafat. "Parallel applications and solutions in artificial intelligence and expert systems." Thesis, Loughborough University, 1991. https://dspace.lboro.ac.uk/2134/13692.
Full textPilon, Mathieu. "A graphic simulator for a robotic workcell programming environment /." Thesis, McGill University, 1991. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=60085.
Full textSimulation, especially graphic simulation, can greatly contribute to the development of programs for such integrated robotic applications: the simulator emulates the behavior of the workcell on a computer display, and allows the programmer to test and debug programs without requiring an immediate access to the physical equipment.
This thesis presents the design of a graphic simulator for robotic workcell applications. The simulator is based on SAGE/WRAP, an environment for the programming and run-time control of robotic workcells. Given a WRAP program as input, the simulator displays a top-view of the workcell and animates graphically the execution of the program; the coordination and the flow of operations within the workcell being shown, the programmer can quickly assess the overall validity of the program.
The simulator was developed in C under the X Window System, and is currently implemented as a standalone software; the design was made flexible and modular, to facilitate an eventual integration to the WRAP environment.
Heaton, Jeff. "Automated Feature Engineering for Deep Neural Networks with Genetic Programming." Thesis, Nova Southeastern University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10259604.
Full textFeature engineering is a process that augments the feature vector of a machine learning model with calculated values that are designed to enhance the accuracy of a model's predictions. Research has shown that the accuracy of models such as deep neural networks, support vector machines, and tree/forest-based algorithms sometimes benefit from feature engineering. Expressions that combine one or more of the original features usually create these engineered features. The choice of the exact structure of an engineered feature is dependent on the type of machine learning model in use. Previous research demonstrated that various model families benefit from different types of engineered feature. Random forests, gradient-boosting machines, or other tree-based models might not see the same accuracy gain that an engineered feature allowed neural networks, generalized linear models, or other dot-product based models to achieve on the same data set.
This dissertation presents a genetic programming-based algorithm that automatically engineers features that increase the accuracy of deep neural networks for some data sets. For a genetic programming algorithm to be effective, it must prioritize the search space and efficiently evaluate what it finds. This dissertation algorithm faced a potential search space composed of all possible mathematical combinations of the original feature vector. Five experiments were designed to guide the search process to efficiently evolve good engineered features. The result of this dissertation is an automated feature engineering (AFE) algorithm that is computationally efficient, even though a neural network is used to evaluate each candidate feature. This approach gave the algorithm a greater opportunity to specifically target deep neural networks in its search for engineered features that improve accuracy. Finally, a sixth experiment empirically demonstrated the degree to which this algorithm improved the accuracy of neural networks on data sets augmented by the algorithm's engineered features.
Glossenger, John Kenneth. "The role of planning in two artificial intelligence architectures." Instructions for remote access. Click here to access this electronic resource. Access available to Kutztown University faculty, staff, and students only, 1991. http://www.kutztown.edu/library/services/remote_access.asp.
Full textTebbutt, Colin Dean. "Control system design using artificial intelligence." Doctoral thesis, University of Cape Town, 1991. http://hdl.handle.net/11427/14697.
Full textSuccessful multivariable control system design demands knowledge, skill and creativity of the designer. The goal of the research described in this dissertation was to investigate, implement, and evaluate methods by which artificial intelligence techniques, in a broad sense, may be used in a design system to assist the user. An intelligent, interactive, control system design tool has been developed to fulfil this aim. The design tool comprises two main components; an expert system on the upper level, and a powerful CACSD package on the lower level. The expert system has been constructed to assist and guide the designer in using the facilities provided by the underlying CACSD package. Unlike other expert systems, the user is also aided in formulating and refining a comprehensive and achievable design specification, and in dealing with conflicts which may arise within this specification. The assistance is aimed at both novice and experienced designers. The CACSD package includes a synthesis program which attempts to find a controller that satisfies the design specification. The synthesis program is based upon a recent factorization theory approach, where the linear multivariable control system design problem is translated into, and techniques efficiency solved as, a quadratic programming problem, which significantly improve the time and space of this method have been developed, making it practical to solve substantial multivariable design problems using only a microcomputer. The design system has been used by students at the University of Cape Town. Designs produced using the expert system tool are compared against those produced using classical design methods.
Quek, Hiok Chai. "The application of artificial intelligence techniques to the integrated control of complex dynamic physical systems." Thesis, Heriot-Watt University, 1990. http://hdl.handle.net/10399/924.
Full textKeflas, Petros. "Brave : an OR-parallel logic language and its application to search problems in artificial intelligence." Thesis, University of Essex, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.290744.
Full textBooks on the topic "Artificial intelligence. Computer programming"
1968-, Funge John David, ed. Artificial intelligence for games. 2nd ed. Elsevier Morgan Kaufmann, 2009.
Calero, Pedro A. González. Artificial Intelligence for Computer Games. Springer Science+Business Media, LLC, 2011.
Hasemer, Tony. Common LISP programming for artificial intelligence. Addison-Wesley, 1989.
Shafer, Dan. Artificial intelligence programming for the Macintosh. H.W. Sams, 1986.
Prolog programming for artificial intelligence. 3rd ed. Addison Wesley, 2001.
Prolog programming for artificial intelligence. 4th ed. Addison-Wesley, 2011.
Ivan, Bratko. Prolog programming for artificial intelligence. 2nd ed. Addison-Wesley Pub. Co., 1991.
Prolog programming for artificial intelligence. Addison-Wesley, 1986.
Prolog programming for artificial intelligence. 2nd ed. Addison-Wesley Pub. Co., 1990.
Ivan, Bratko. Prolog programming for artificial intelligence. 2nd ed. Addison-Wesley Pub. Co, 1990.
Book chapters on the topic "Artificial intelligence. Computer programming"
Arvind, Steve Heller, and Rishiyur S. Nikhil. "Programming Generality and Parallel Computers." In Biological and Artificial Intelligence Systems. Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-3117-6_16.
Full textde Souza, Gabriel Henrique, Heder Soares Bernardino, Alex Borges Vieira, and Helio José Corrêa Barbosa. "Genetic Programming for Feature Extraction in Motor Imagery Brain-Computer Interface." In Progress in Artificial Intelligence. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86230-5_18.
Full textMcMath, David, Marianna Rozenfeld, and Richard Sommer. "A Computer Environment for Writing Ordinary Mathematical Proofs." In Logic for Programming, Artificial Intelligence, and Reasoning. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45653-8_35.
Full textColtell, Óscar, and José Ma Ordovás. "Applying object logic programming to design computer strategies in gene scanning." In Tasks and Methods in Applied Artificial Intelligence. Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-64574-8_448.
Full textLenat, Doug. "Scaling Up: Computers vs. Common Sense." In Logic for Programming, Artificial Intelligence, and Reasoning. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11591191_4.
Full textLlerena-Izquierdo, Joe, and Jonathan Zamora-Galindo. "Using H5P Services to Enhance the Student Evaluation Process in Programming Courses at the Universidad Politécnica Salesiana (Guayaquil, Ecuador)." In Artificial Intelligence, Computer and Software Engineering Advances. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68080-0_16.
Full textBengio, Yoshua, Emma Frejinger, Andrea Lodi, Rahul Patel, and Sriram Sankaranarayanan. "A Learning-Based Algorithm to Quickly Compute Good Primal Solutions for Stochastic Integer Programs." In Integration of Constraint Programming, Artificial Intelligence, and Operations Research. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58942-4_7.
Full textGalindo, Mauricio Javier Osorio, and Luis Angel Montiel Moreno. "Creative Composition Problem: A Knowledge Graph Logical-Based AI Construction and Optimization Solution." In Lecture Notes in Computer Science. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72308-8_4.
Full textBalducelli, Claudio, and Massimo Gallanti. "Developing an Expert System for Fault Diagnosis of a Turbo Generator Group Using an OPS5 Production Rules Programming Environment." In Artificial Intelligence and Other Innovative Computer Applications in the Nuclear Industry. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4613-1009-9_68.
Full textPérez Castaño, Arnaldo. "Game Programming." In Practical Artificial Intelligence. Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3357-3_15.
Full textConference papers on the topic "Artificial intelligence. Computer programming"
Zhao, Xin, Kai Lu, and Xiao-Ping Wang. "A Programming Abstraction for R in Distributed Parallel System." In International Conference on Computer Science and Artificial Intelligence (CSAI2016). WORLD SCIENTIFIC, 2017. http://dx.doi.org/10.1142/9789813220294_0047.
Full textShao, Qing, Jianbo Wang, Qingbin Yu, Tao Xu, and Yoshino Tatsuo. "An IB-PSO algorithm for unconstrained nonlinear programming problems." In 2021 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA). IEEE, 2021. http://dx.doi.org/10.1109/icaica52286.2021.9498010.
Full textJinhui, Yuan, Zhou Hongwei, and Zhang Laisun. "RSGX: Defeating SGX Side Channel Attack with Return Oriented Programming." In 2021 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA). IEEE, 2021. http://dx.doi.org/10.1109/icaica52286.2021.9498147.
Full textHuo, Manyan, Yue Yu, Zhixing Li, and Junsheng Chang. "Predicting Programming Behavior in OSS Communities: A Case Study of NLP-based Approach." In 2020 International Conference on Artificial Intelligence and Computer Engineering (ICAICE). IEEE, 2020. http://dx.doi.org/10.1109/icaice51518.2020.00091.
Full textTarzariol, Alice, Martin Gebser, and Konstantin Schekotihin. "Lifting Symmetry Breaking Constraints with Inductive Logic Programming." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/284.
Full textZhu, Hongyuan, Xi Peng, Vijay Chandrasekhar, Liyuan Li, and Joo-Hwee Lim. "DehazeGAN: When Image Dehazing Meets Differential Programming." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/172.
Full textDu, Qing, Wei Zheng, and Chuanlin Xia. "Question Difficulty Priori Evaluation Based on Fuzzy Logic in Programming System." In 2021 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA). IEEE, 2021. http://dx.doi.org/10.1109/icaica52286.2021.9498258.
Full textWolfer, James. "Topical tapestry: Weaving threads of parallel programming, computer graphics, and artificial intelligence into undergraduate CS courses." In 2014 IEEE Global Engineering Education Conference (EDUCON). IEEE, 2014. http://dx.doi.org/10.1109/educon.2014.6826219.
Full textSchmoll, Sebastian, and Matthias Schubert. "Dynamic Resource Routing using Real-Time Dynamic Programming." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/670.
Full textEne, Alexandru, and Cosmin Stirbu. "Automatic generation of quizzes for Java programming language." In 2019 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI). IEEE, 2019. http://dx.doi.org/10.1109/ecai46879.2019.9042052.
Full textReports on the topic "Artificial intelligence. Computer programming"
Fogel, Lawrence J., and David Fogel. Artificial Intelligence through Evolutionary Programming: Prediction and Identification. Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada171544.
Full textDanner, William F. The use of artificial intelligence programming techniques for communication between incompatible building information systems. National Bureau of Standards, 1987. http://dx.doi.org/10.6028/nbs.ir.87-3529.
Full textHofer, Martin, Tomas Sako, Arturo Martinez Jr., et al. Applying Artificial Intelligence on Satellite Imagery to Compile Granular Poverty Statistics. Asian Development Bank, 2020. http://dx.doi.org/10.22617/wps200432-2.
Full textRodriguez, Simon, Autumn Toney, and Melissa Flagg. Patent Landscape for Computer Vision: United States and China. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/20200054.
Full textMurdick, Dewey, Daniel Chou, Ryan Fedasiuk, and Emily Weinstein. The Public AI Research Portfolio of China’s Security Forces. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/20200057.
Full textRaychev, Nikolay. Can human thoughts be encoded, decoded and manipulated to achieve symbiosis of the brain and the machine. Web of Open Science, 2020. http://dx.doi.org/10.37686/nsrl.v1i2.76.
Full textAmbitious Mashups: Reflections on a Decade of Cyberlearning Research. Digital Promise, 2020. http://dx.doi.org/10.51388/20.500.12265/105.
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