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Towards a Simulation-Based Programming Paradigm for AI applications [article]

Jörg Pührer
2015 arXiv   pre-print
We present initial ideas for a programming paradigm based on simulation that is targeted towards applications of artificial intelligence (AI).  ...  We define basic notions of a simulation-based programming paradigm and show how it can be used for implementing AI applications.  ...  Next, we introduce the basic notions of a simulation-based programming paradigm. Section 3 discusses how to model different scenarios of AI applications in the approach.  ... 
arXiv:1505.05373v1 fatcat:mrgpwclx2zaxdkrqv6g5gxlecu

MDE4QAI: Towards Model-Driven Engineering for Quantum Artificial Intelligence [article]

Armin Moin, Moharram Challenger, Atta Badii, Stephan Günnemann
2022 arXiv   pre-print
In the decade ahead, an unprecedented paradigm shift from classical computing towards Quantum Computing (QC), with perhaps a quantum-classical hybrid model, is expected.  ...  In this paper, the vision is focused on MDE for Quantum AI, particularly Quantum ML for the Internet of Things (IoT) and smart Cyber-Physical Systems (CPS) applications.  ...  Acknowledgment The authors would like to thank Dalibor Hrg for sharing the insights. Bibliography  ... 
arXiv:2107.06708v2 fatcat:l4ykddnlqzf75glmszuyzfqfzm

Page 174 of University Computing : The Bulletin of the IUCC Vol. 12, Issue 4 [page]

1990 University Computing : The Bulletin of the IUCC  
Knowledge-based simulation is a combination of AI knowledge representation schemes and discrete event simulation.  ...  In this book the author follows on from earlier theoretical work in knowledge-based simulation by describing an implementation in DEVS-Scheme —an environment for simulation and model construction based  ... 

Language (Re)modelling: Towards Embodied Language Understanding [article]

Ronen Tamari, Chen Shani, Tom Hope, Miriam R. L. Petruck, Omri Abend, Dafna Shahaf
2020 arXiv   pre-print
This position paper argues that the use of grounding by metaphoric inference and simulation will greatly benefit NLU systems, and proposes a system architecture along with a roadmap towards realizing this  ...  According to ECL, natural language is inherently executable (like programming languages), driven by mental simulation and metaphoric mappings over hierarchical compositions of structures and schemata learned  ...  Acknowledgments We thank the reviewers for their insightful comments.  ... 
arXiv:2005.00311v2 fatcat:giwy3vxpazd73m5nmvj7lwo32e

Theatre, Perception, Symbol

Daniel Sonntag
2011 Künstliche Intelligenz  
When I began to study computational linguistics and artificial intelligence in the mid-nineties, I liked such sayings, like this one: computational linguistics deals with computer programs for parsing  ...  A theatre researcher, however, might add to Goethe's words that not only the staging itself, but the usage of specific linguistic or visual metaphors, i.e., the  ...  Topics of interest include but are not limited to: • Classical and new paradigms of AI programming • Functional-logic, constraint-based, and further multiparadigm languages  ... 
doi:10.1007/s13218-011-0117-8 fatcat:v7c5uj7vfjdmdknysqb2mli47i

Artificial Intelligence + Distributed Systems = Agents

Ioan Dzitac, Boldur E. Bărbat
2009 International Journal of Computers Communications & Control  
technology and semantic web, applications - running in open, heterogeneous, dynamic and uncertain environments-current paradigms are not enough, because of the shift from programs to processes.  ...  Among the conclusions: a) Nondeterministic software is unavoidable; its development entails not just new design principles but new computing paradigms. b) Agent-oriented systems, to be effectual, should  ...  Hence the rationale is threefold, depending on the perspective: a) AI (intelligent software must be process-based, not program-based); b) Software engineering (intelligent applications should be agent-oriented  ... 
doi:10.15837/ijccc.2009.1.2410 fatcat:f75nvipq2ja6bddgjk5swcqs2a

The Next Big Thing: Position Statements

Munindar P. Singh, Daniel G. Bobrow, Michael N. Huhns, Margaret King, Hiroaki Kitano
1997 International Joint Conference on Artificial Intelligence  
This panel is a celebration of artificial intelligence (AI).  ...  Basing its claims to interest on the past accomplishments of AI, it highlights some of the new exciting concepts and technologies that compete for the title The Next Big Thing.  ...  Declarative paradigm: functional and logic programming 3. Interactive paradigm: object-based and distributed programming.  ... 
dblp:conf/ijcai/SinghBHKK97 fatcat:jpfr5242fnbnfgycyyc32tti74

Materials science and engineering: New vision in the era of artificial intelligence [article]

Tao Qiang, Honghong Gao
2018 arXiv   pre-print
This work will help to address the global challenge for materials discovery in the era of artificial intelligence (AI), and essentially contribute to accelerating future materials continuum.  ...  Scientific discovery evolves from the experimental, through the theoretical and computational, to the current data-intensive paradigm.  ...  Zhou for their in-depth discussion and valuable comments.  ... 
arXiv:1804.08293v1 fatcat:d2zygxzji5e35gy2g73dyve7ei

A Review of Agent-Based Programming for Multi-Agent Systems

Rafael C. Cardoso, Angelo Ferrando
2021 Computers  
In this paper, we focus on agent programming and we provide a systematic review of the literature in agent-based programming for multi-agent systems.  ...  It encompasses a multitude of techniques, such as negotiation protocols, agent simulation, multi-agent argumentation, multi-agent planning, and many others.  ...  LightJason, a highly scalable Java-based platform for BDI agent-oriented programming and simulation is presented in [34] .  ... 
doi:10.3390/computers10020016 fatcat:z6ebckw62javvfbi6dgobmpd4m

Integration of simulation and optimization for solving complex decision making problems

S. Iassinovski, A. Artiba, V. Bachelet, F. Riane
2003 International Journal of Production Economics  
We give the general approach of our methodology and then describe the way we integrate simulation and optimization for solving decision making problems.  ...  This paper concerns the development of an unified formal modeling framework designed to provide for model sharing, reusability and integration of simulation and optimization methods in order to allow the  ...  Obviously, a hybrid tool based on a unique system representation for simulation, optimisation and decision making would be preferable.  ... 
doi:10.1016/s0925-5273(03)00082-3 fatcat:j7qpizwwb5ewdfgth2yzwes7oa

AI-coupled HPC Workflows [article]

Shantenu Jha, Vincent R. Pascuzzi, Matteo Turilli
2022 arXiv   pre-print
The increasing need of coupling AI/ML and HPC across scientific domains is motivated, and then exemplified by a number of production-grade use cases for each mode.  ...  While both HPC workflow and AI/ML computing paradigms are independently effective, we highlight how their integration, and ultimate convergence, is leading to significant improvements in scientific performance  ...  Acknowledgements The authors would like to thank Jack Well and Tom Gibbs (NVIDIA), and Addi Malviya Thakur (ORNL) for valuable suggestions on early drafts. SJ acknowledges Geoffrey Fox for many  ... 
arXiv:2208.11745v1 fatcat:fr5y2au7jbardjzrbikayz366y

Grand Challenges in Pedometrics-AI Research

Sabine Grunwald
2021 Frontiers in Soil Science  
Artificial intelligence (AI), specifically machine learning (ML), and deep learning (DL) algorithms, have advanced a profound transformation of the discipline with new challenges.  ...  This latter mental frame accounts for soil-landscape conditions (STEP factors iii ) and the dynamics of the atmosphere/climate (A), water/hydrosphere (W), biosphere (B), as well as human activities (H)  ...  ACKNOWLEDGMENTS I would like to thank the critical discussion within the Pedometrics Commission of the International Union of Soil Science for the inspiration to write this short article.  ... 
doi:10.3389/fsoil.2021.714323 fatcat:esp4js65lbfetciby3ltd7o3zm

Artificial intelligence for object-oriented software engineering

Dennis de Champeaux, Hermann Kaindl, Joachim Laubsch, Albert Schappert
1994 Addendum to the proceedings on Object-oriented programming systems, languages, and applications (Addendum) - OOPSLA '94  
The requirement of software engineering in AI is for increased modularity, re-use ability and maintainability in the software which has accentuated interest in the object-oriented programming paradigm.  ...  For instance, can a computer diagnose a disease based on the symptoms the person exhibits? This is why artificial intelligence steps in. It allows the computer to think like human.  ...  For example, artificial intelligences (AI) and expert system are some application built using OOP techniques [5, 6] .  ... 
doi:10.1145/260028.260173 fatcat:bu2mjqbfgrh47jedqlxiagtsau

Evolution of artificial intelligence languages, a systematic literature review [article]

Emmanuel Adetiba, Temitope John, Adekunle Akinrinmade, Funmilayo Moninuola, Oladipupo Akintade, Joke Badejo
2021 arXiv   pre-print
In order to analyze the state of the art of research in the field of AI, we present a systematic literature review focusing on the Evolution of AI programming languages.  ...  This review provides information on the year of implementation, development team, capabilities, limitations and applications of each of the AI programming languages discussed.  ...  Acknowledgement The authors wish to acknowledge the Covenant University Center for Research, Innovation and Discovery (CUCRID) for providing fund towards the publication of this study.  ... 
arXiv:2101.11501v1 fatcat:b3xvk5aeevgjlli6r2yo2d6hey

Artificial Intelligence and Its Application in Optimization under Uncertainty [chapter]

Saeid Sadeghi, Maghsoud Amiri, Farzaneh Mansoori Mooseloo
2021 Artificial Intelligence  
Perspectives on reinforcement learning (RL)-based data-driven optimization and deep RL for solving NP-hard problems are discussed.  ...  Then, a comprehensive review and classification of the relevant publications on the data-driven stochastic program, data-driven robust optimization, and data-driven chance-constrained are presented.  ...  Thus, AI techniques are applied to big data sources to extract the knowledge-based rules or identify the underlying rules and patterns by ML techniques, to drive the systems toward set objectives.  ... 
doi:10.5772/intechopen.98628 fatcat:mtbuaqghgvha3fa64osyahca2q
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