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Artykuły w czasopismach na temat "BDI Logics"
Grabovskis, Arvids, i Janis Grundspenkis. "Identification of Relations between BDI Logic and BDI Agents". Scientific Journal of Riga Technical University. Computer Sciences 44, nr 1 (1.01.2011): 21–28. http://dx.doi.org/10.2478/v10143-011-0018-1.
Pełny tekst źródłaHerzig, Andreas, Emiliano Lorini, Laurent Perrussel i Zhanhao Xiao. "BDI Logics for BDI Architectures: Old Problems, New Perspectives". KI - Künstliche Intelligenz 31, nr 1 (18.10.2016): 73–83. http://dx.doi.org/10.1007/s13218-016-0457-5.
Pełny tekst źródłaRao, A. "Decision procedures for BDI logics". Journal of Logic and Computation 8, nr 3 (1.06.1998): 293–342. http://dx.doi.org/10.1093/logcom/8.3.293.
Pełny tekst źródłaBenrouba, Ferdaous, i Rachid Boudour. "A Model Combining BDI Logic and Temporal Logics for Decision-Making in Emergency". International Journal of Advances in Soft Computing and its Applications 14, nr 3 (28.11.2022): 32–48. http://dx.doi.org/10.15849/ijasca.221128.03.
Pełny tekst źródłaDziubiński, Marcin. "Modal context restriction for multiagent BDI logics". Artificial Intelligence Review 55, nr 4 (6.10.2021): 3075–151. http://dx.doi.org/10.1007/s10462-021-10064-6.
Pełny tekst źródłaNaoyuki, Nide, Shiro Takata i Tadashi Araragi. "Deduction Systems for BDI Logics with Mental State Consistency". Electronic Notes in Theoretical Computer Science 70, nr 5 (październik 2002): 140–52. http://dx.doi.org/10.1016/s1571-0661(04)80593-0.
Pełny tekst źródłaPetik, Jaroslav. "PHILOSOPHICAL PROBLEMS OF THE MENTALISTIC LOGIC". Sophia. Human and Religious Studies Bulletin 14, nr 2 (2019): 38–43. http://dx.doi.org/10.17721/sophia.2019.14.9.
Pełny tekst źródłaLARCHEY-WENDLING, DOMINIQUE, i DIDIER GALMICHE. "Exploring the relation between Intuitionistic BI and Boolean BI: an unexpected embedding". Mathematical Structures in Computer Science 19, nr 3 (czerwiec 2009): 435–500. http://dx.doi.org/10.1017/s0960129509007567.
Pełny tekst źródłaCruz, Anderson, André V. dos Santos, Regivan H. N. Santiago i Benjamin Bedregal. "A Fuzzy Semantic for BDI Logic". Fuzzy Information and Engineering 13, nr 2 (3.04.2021): 139–53. http://dx.doi.org/10.1080/16168658.2021.1915455.
Pełny tekst źródłaBlee, Jeff, David Billington, Guido Governatori i Abdul Sattar. "Levels of modality for BDI Logic". Journal of Applied Logic 9, nr 4 (grudzień 2011): 250–73. http://dx.doi.org/10.1016/j.jal.2011.08.002.
Pełny tekst źródłaRozprawy doktorskie na temat "BDI Logics"
Nair, Vineet, i n/a. "On Extending BDI Logics". Griffith University. School of Information Technology, 2003. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20030929.095254.
Pełny tekst źródłaBirštunas, Adomas. "Sequent calculi with an efficient loop-check for BDI logics". Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2010. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2010~D_20100302_095327-67575.
Pełny tekst źródłaDarbe nagrinėjami sekvenciniai skaičiavimai BDI logikoms. BDI logikos yra plačiai naudojamos agentinių sistemų aprašymui ir realizavimui. Agentai yra autonomiškos sistemos, kurios veikia kažkurioje aplinkoje ir siekia įvykdyti iš anksto apibrėžtus tikslus. Sprendimų priėmimo realizavimas yra svarbiausia ir sudėtingiausia dalis realizuojant agentines sistemas. Sprendimo priėmimo realizavimui gali būti naudojami logikos skaičiavimai. Šiame darbe ir yra nagrinėjami sekvenciniai skaičiavimai BDI logikoms. BDI logikose, kaip ir kitose modalumo logikose, yra naudojama ciklų paieška išsprendžiamumui gauti. Neefektyvi ciklų paieška užima didesnę išvedimų paieškos resursų dalį. Kai kurioms modalumo logikoms yra žinomi becikliai skaičiavimai ar skaičiavimai naudojantys efektyvią ciklų paiešką. Šiame darbe yra pateikiamas beciklis sekvencinis skaičiavimas KD45 logikai, kuri yra esminis BDI logikų fragmentas. Pateiktas skaičiavimas ne tik eliminuoja ciklų paiešką, bet ir supaprastina patį sekvencijos išvedimą. Skaidaus laiko logikai (kitam BDI logikų fragmentui) yra pateikiamas sekvencinis skaičiavimas naudojantis efektyvią ciklų paiešką. Gauti rezultatai yra pritaikyti sukuriant sekvencinius skaičiavimus vianaagentinei ir daugiaagentinei BDI logikoms. Pristatyti skaičiavimai naudoja tik apribotą ciklų paiešką. Be to, kai kurių tipų ciklus eliminuoja visiškai. Šie rezultatai įgalina kurti efektyvesnes agentines sistemas, paremtas BDI logikomis.
Xiao, Zhanhao. "Raffinement des intentions". Thesis, Toulouse 1, 2017. http://www.theses.fr/2017TOU10051/document.
Pełny tekst źródłaBirštunas, Adomas. "Sekvenciniai skaičiavimai BDI logikoms su efektyvia ciklų paieška". Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2010. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2010~D_20100302_095338-77193.
Pełny tekst źródłaSequent calculi for BDI logics is a research object of the thesis. BDI logics are widely used for agent system description and implementation. Agents are autonomous systems, those acts in some environment and aspire to achieve preassigned goals. Implementation of the decision making is the main and the most complicated part in agent systems implementation. Logic calculi may be used for the decision making implementation. In this thesis, there are researched sequent calculi for BDI logics. Sequent calculi for BDI logics, like sequent calculi for other modal logics, use loop-check technique to get decidability. Inefficient loop-check takes a major part of the resources used for the derivation. For some modal logics, there are known loop-check free sequent calculi or calculi with an efficient loop-check. In this thesis, there is presented loop-check free sequent calculus for KD45 logic, which is the main fragment of the BDI logics. Introduced calculus not only eliminates loop-check, but also simplifies sequent derivation. For the branching time logic (another BDI logic fragment) there is presented sequent calculus with an efficient loop-check. Obtained results are adapted for creation sequent calculi for monoagent and multiagent BDI logics. Introduced calculi use only restricted loop-check. Moreover, loop-check is totally eliminated for some types of the loops. These results enables to create more efficient agent systems, those are based on the BDI logics.
Forti, Maicol. "Logic Reasoning in BDI Agents: Current Trends and Spatial Integrations". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/23426/.
Pełny tekst źródłaCruz, Anderson Paiva. "L?gica BDI fuzzy". Universidade Federal do Rio Grande do Norte, 2008. http://repositorio.ufrn.br:8080/jspui/handle/123456789/17995.
Pełny tekst źródłaCoordena??o de Aperfei?oamento de Pessoal de N?vel Superior
Intendding to understand how the human mind operates, some philosophers and psycologists began to study about rationality. Theories were built from those studies and nowadays that interest have been extended to many other areas such as computing engineering and computing science, but with a minimal distinction at its goal: to understand the mind operational proccess and apply it on agents modelling to become possible the implementation (of softwares or hardwares) with the agent-oriented paradigm where agents are able to deliberate their own plans of actions. In computing science, the sub-area of multiagents systems has progressed using several works concerning artificial intelligence, computational logic, distributed systems, games theory and even philosophy and psycology. This present work hopes to show how it can be get a logical formalisation extention of a rational agents architecture model called BDI (based in a philosophic Bratman s Theory) in which agents are capable to deliberate actions from its beliefs, desires and intentions. The formalisation of this model is called BDI logic and it is a modal logic (in general it is a branching time logic) with three access relations: B, D and I. And here, it will show two possible extentions that tranform BDI logic in a modal-fuzzy logic where the formulae and the access relations can be evaluated by values from the interval [0,1]
Com o intuito de entender como a mente humana funciona iniciaram-se estudos sobre cogni??o nos campos da filosofia e psicologia. Teorias surgiram desses estudos e, atualmente, esta curiosidade foi estendida a outras ?reas, tais como, ci?ncia e engenharia de computa??o, no entanto, nestas ?reas, o objetivo ? sutilmente diferente: entender o funcionamento da mente e aplic?-lo em uma modelagem artificial. Em ci?ncia da computa??o, a sub-?rea de sistemas multiagentes tem progredido bastante, utilizando trabalhos em intelig?ncia artificial, l?gica computacional, sistemas distribu?dos, teoria dos jogos e, aproveitando tamb?m teorias provenientes da pr?pria filosofia e psicologia. Desta forma, alguns pesquisadores j? v?em o paradigma de programa??o orientado a agentes como a melhor solu??o para a implementa??o dos softwares mais complexos: cujos sistemas s?o din?micos, n?o-determin?sticos e que podem ter de operar com dados faltosos sobre ambientes tamb?m din?micos e n?o-determin?sticos. Este trabalho busca a apresenta??o de uma extens?o da formaliza??o l?gica de um modelo de arquitetura de agentes cognitivos, chamado BDI (belief-desire-intention), na qual o agente ? capaz de deliberar suas a??es baseando-se em suas cren?as, desejos e inten??es. A formaliza??o de tal modelo ? conhecida pelo nome de l?gica BDI, uma l?gica modal com tr?s rela??es de modalidade. Neste trabalho, ser?o apresentados dois planos para transform?-la numa l?gica modal fuzzy onde as rela??es de acessibilidade e as f?rmulas (modais-fuzzy) poder?o ter valora??es dentro do intervalo [0,1]. Esta l?gica modal fuzzy h? de ser um sistema l?gico formal capaz de representar quantitativamente os diferentes graus de cren?as, desejos e inten??es objetivando a constru??o de racioc?nios fuzzy e a delibera??o de a??es de um agente (ou grupo de agentes), atrav?s dessas atitudes mentais (seguindo assim um modelo intensional)
Mora, Michael da Costa. "Um Modelo formal e executável de agentes BDI". reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 1999. http://hdl.handle.net/10183/3955.
Pełny tekst źródłaSouza, Marlo Vieira dos Santos e. "Choices that make you chnage your mind : a dynamic epistemic logic approach to the semantics of BDI agent programming languages". reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2016. http://hdl.handle.net/10183/150039.
Pełny tekst źródłaAs the notions of Agency and Multiagent System became important topics for the Computer Science and Artificial Intelligence communities, Agent Programming has been proposed as a paradigm for the development of computer systems. As such, in the last decade, we have seen the flourishing of the literature on Agent Programming with the proposal of several programming languages, e.g. AgentSpeak (RAO, 1996; BORDINI; HUBNER;WOOLDRIDGE, 2007), Jadex (POKAHR; BRAUBACH; LAMERSDORF, 2005), JACK (HOWDEN et al., 2001), 3APL/2APL (DASTANI; VAN RIEMSDIJK; MEYER, 2005; DASTANI, 2008), GOAL (HINDRIKS et al., 2001), among others. Agent Programming is a programming paradigm proposed by Shoham (1993) in which the minimal units are agents. An agent is an entity composed of mental attitudes, that describe the its internal state - such as its motivations and decisions - as well as its relation to the external world - its beliefs about the world, its obligations, etc. This programming paradigm stems from the work on Philosophy of Action and Artificial Intelligence concerning the notions of intentional action and formal models of agents’ mental states. As such, the meaning (and properties) of notions such as belief, desire, intention, etc. as studied in these disciplines are of central importance to the area. Particularly, we will concentrate in our work on agent programming languages influenced by the so-called BDI paradigm of agency, in which an agent is described by her beliefs, desires, intentions. While the engineering of such languages has been much discussed, the connections between the theoretical work on Philosophy and Artificial Intelligence and its implementations in programming languages are not so clearly understood yet. This distance between theory and practice has been acknowledged in the literature for agent programming languages and is commonly known as the “semantic gap”. Many authors have attempted to tackle this problem for different programming languages, as for the case of AgentSpeak (BORDINI; MOREIRA, 2004), GOAL (HINDRIKS; VAN DER HOEK, 2008), etc. In fact, Rao (1996, p. 44) states that “[t]he holy grail of BDI agent research is to show such a one-to-one correspondence with a reasonably useful and expressive language.” One crucial limitation in the previous attempts to connect agent programming languages and BDI logics, in our opinion, is that the connection is mainly established at the static level, i.e. they show how a given program state can be interpreted as a BDI mental state. It is not clear in these attempts, however, how the execution of the program may be understood as changes in the mental state of the agent. The reason for this, in our opinion, is that the formalisms employed to construct BDI logics are usually static, i.e. cannot represent actions and change, or can only represent ontic change, not mental change. The act of revising one’s beliefs or adopting a given desire are mental actions (or internal actions) and, as such, different from performing an action over the environment (an ontic or external action). This difference is well recognized in the literature on the semantics of agent programming languages (D’INVERNO et al., 1998; BORDINI; HUBNER; WOOLDRIDGE, 2007; MENEGUZZI; LUCK, 2009), but this difference is lost when translating their semantics into a BDI logic. We believe the main reason for that is a lack of expressibility in the formalisms used to model BDI reasoning. Dynamic Epistemic Logic, or DEL, is a family of dynamic modal logics to study information change and the dynamics of mental attitudes inspired by the Dutch School on the “dynamic turn” in Logic (VAN BENTHEM, 1996). This formalism stems from various approaches in the study of belief change and differs from previous studies, such as AGM Belief Revision, by shifting from extra-logical characterization of changes in the agents attitudes to their integration within the representation language. In the context of Dynamic Epistemic Logic, the Dynamic Preference Logic of Girard (2008) seems like an ideal candidate, having already been used to study diverse mental attitudes, such as Obligations (VAN BENTHEM; GROSSI; LIU, 2014), Beliefs (GIRARD; ROTT, 2014), Preferences (GIRARD, 2008), etc. We believe Dynamic Preference Logic to be the ideal semantic framework to construct a formal theory of BDI reasoning which can be used to specify an agent programming language semantics. The reason for that is that inside this logic we can faithfully represent the static state of a agent program, i.e. the agent’s mental state, as well as the changes in the state of the agent program by means of the agent’s reasoning, i.e. by means of her mental actions. As such, in this work we go further in closing the semantic gap between agent programs and agency theories and explore not only the static connections between program states and possible worlds models, but also how the program execution of a language based on common operations - such as addition/removal of information in the already mentioned bases - may be understood as semantic transformations in the models, as studied in Dynamic Logics. With this, we provide a set of operations for the implementation of agent programming languages which are semantically safe and we connect an agent program execution with the dynamic properties in the formal theory. Lastly, by these connections, we provide a framework to study the dynamics of different mental attitudes, such as beliefs, goals and intentions, and how to reproduce the desirable properties proposed in theories of Agency in a programming language semantics.
Adam, Carole. "Emotions : from psychological theories to logical formalization and implementation in BDI agent". Phd thesis, Toulouse, INPT, 2007. http://ethesis.inp-toulouse.fr/archive/00000513/.
Pełny tekst źródłaThis thesis is about emotions, and more particularly about their logical formalization. The first part is dedicated to the state of the art, from the point of view of both psychology (history of theories of emotions) and computer science (presentation of emotional agents and their applications). The second aprt is dedicated to the logical formalisation of emotions. It introduces our logical framework, exposes and argues the formal definitions of twenty emotions, and proves some of their properties. Finally the last part is dedicated to practical applications and continuation prospects of this work. Such a work offers interesting contributions: it offers to the agent community a formal model of a great number of emotions; it shows the interest of BDI logics; and it opens research prospects about the dynamics of emotions and their influence on the behaviour of agents, a field not much explored for now
Adam, Carole Herzig Andréas. "Emotions from psychological theories to logical formalization and implementation in BDI agent /". Toulouse : INP Toulouse, 2008. http://ethesis.inp-toulouse.fr/archive/00000513.
Pełny tekst źródłaKsiążki na temat "BDI Logics"
Beijing Shi she hui ke xue jie lian he hui i Beijing Shi luo ji xue hui, red. Luo ji xue bai nian. Beijing: Beijing chu ban she, 1999.
Znajdź pełny tekst źródłaBai ma fei ma: Zhongguo ming bian si chao. [Beijing]: Xin hua chu ban she, 1993.
Znajdź pełny tekst źródłaLuo ji si wei: Mi mang shi dai de ming bai ren. Beijing: Bei jing lian he chu ban gong si, 2015.
Znajdź pełny tekst źródłaTshad ma rnam ʼgrel gyi dgoṅs don legs par bśad pa blo gsal ʼjug bde lam bu. [Lanzhou]: Kan-suʼu mi rigs dpe skrun khaṅ, 1999.
Znajdź pełny tekst źródłaTshad ma rig paʼi rmaṅ gźiʼi śes bya byis ʼjug bde lam źes bya ba bźugs so. Lhassa: Bod-ljoṅs mi dmaṅs dpe skrun khaṅ, 2011.
Znajdź pełny tekst źródłaDingfu, Ni, red. Jin Yuelin jie du "Mule ming xue": Ji nian Jin Yuelin xian sheng dan chen yi bai yi shi zhou nian. Beijing: Zhongguo she hui ke xue chu ban she, 2005.
Znajdź pełny tekst źródłashi, PCuSER yan jiu, red. Dian nao tu jie da bai ke: How computers work. Taibei Shi: Dian nao ren wen hua, 2004.
Znajdź pełny tekst źródłaWu, Dennis. Towards scalable BDD-based logic synthesis. 2005.
Znajdź pełny tekst źródłaWu, Dennis. Towards scalable BDD-based logic synthesis. 2005.
Znajdź pełny tekst źródłaAltrock, Constantin von, i Hans-Jürgen Zimmermann. Fuzzy Logic, 3 Bde., Bd.2, Anwendungen. Oldenbourg, 1995.
Znajdź pełny tekst źródłaCzęści książek na temat "BDI Logics"
Governatori, Guido, Vineet Padmanabhan i Abdul Sattar. "On Fibring Semantics for BDI Logics". W Logics in Artificial Intelligence, 198–210. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45757-7_17.
Pełny tekst źródłaPadmanabhan, Vineet, i Guido Governatori. "On Constructing Fibred Tableaux for BDI Logics". W Lecture Notes in Computer Science, 150–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-36668-3_18.
Pełny tekst źródłaSchild, Klaus. "On the Relationship between BDI Logics and Standard Logics of Concurrency". W Intelligent Agents V: Agents Theories, Architectures, and Languages, 47–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-49057-4_4.
Pełny tekst źródłaPadmanabhan, Vineet, Guido Governatori i Abdul Sattar. "Fibred BDI Logics: Completeness Preservation in the Presence of Interaction Axioms". W Lecture Notes in Computer Science, 63–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25725-4_6.
Pełny tekst źródłaFan, Xiaocong, i John Yen. "A Framework for Splitting BDI Agents". W Logic for Programming, Artificial Intelligence, and Reasoning, 160–74. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-36078-6_11.
Pełny tekst źródłaBryant, Randal E., i Marijn J. H. Heule. "Generating Extended Resolution Proofs with a BDD-Based SAT Solver". W Tools and Algorithms for the Construction and Analysis of Systems, 76–93. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72016-2_5.
Pełny tekst źródłaEiter, Thomas, Georg Gottlob i Heikki Mannila. "Disjunctive Logic Programming over Finite Structures". W Innovationen bei Rechen- und Kommunikationssystemen, 69–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-51136-3_10.
Pełny tekst źródłaLoveland, D. W. "Proof Procedures for Disjunctive Logic Programming". W Innovationen bei Rechen- und Kommunikationssystemen, 92. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-51136-3_14.
Pełny tekst źródłaAdam, Carole, Benoit Gaudou, Andreas Herzig i Dominique Longin. "OCC’s Emotions: A Formalization in a BDI Logic". W Artificial Intelligence: Methodology, Systems, and Applications, 24–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11861461_5.
Pełny tekst źródłaBlee, Jeff, David Billington i Abdul Sattar. "Reasoning with Levels of Modalities in BDI Logic". W Agent Computing and Multi-Agent Systems, 410–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01639-4_39.
Pełny tekst źródłaStreszczenia konferencji na temat "BDI Logics"
Naoyuki, NIDE, i Shiro Takata. "Deduction systems for BDI logics using sequent calculus". W the first international joint conference. New York, New York, USA: ACM Press, 2002. http://dx.doi.org/10.1145/544862.544955.
Pełny tekst źródłaBlee, Jeff, David Billington, Guido Governatori i Abdul Sattar. "Levels of Modalities for BDI Logic". W 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. IEEE, 2008. http://dx.doi.org/10.1109/wiiat.2008.231.
Pełny tekst źródłaYuan, Jinping, Aihua Bao, Li Yao, Xuetian Qi i Fang Liu. "Defeasible logic base BDI agent for argumentation". W 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS 2009). IEEE, 2009. http://dx.doi.org/10.1109/icicisys.2009.5357863.
Pełny tekst źródłaXiao, Zhanhao. "Refinement of Intentions". W Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/771.
Pełny tekst źródłaGao, Zi-Xiang, Zi-Li Wang, Yi Ren, De-Zhen Yang, Lin-Lin Liu, Qiang Feng i Bo Sun. "Improved BDD Binary Logic Algorithm: Hidden BDD Algorithm". W 2019 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE). IEEE, 2019. http://dx.doi.org/10.1109/qr2mse46217.2019.9021170.
Pełny tekst źródłaHalac, Tayfun Gokmen, Erdem Eser Ekinci i Oguz Dikenelli. "Description Logic Based BDI Implementation for Goal-Directed Semantic Agents". W 2011 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT). IEEE, 2011. http://dx.doi.org/10.1109/wi-iat.2011.192.
Pełny tekst źródłaChen, Mei, i Xiaohui Hu. "Using Fuzzy Logic as a Reasoning Model for BDI Agents". W 2010 International Conference on Computational Intelligence and Software Engineering (CiSE). IEEE, 2010. http://dx.doi.org/10.1109/cise.2010.5676842.
Pełny tekst źródłaOsman, Nardine, Mark d'Inverno, Carles Sierra, Leila Amgoud, Henri Prade, Matthew Yee-King, Roberto Confalonieri, Dave de Jonge i Katina Hazelden. "An experience-based BDI logic: Motivating shared experiences and intentionality". W IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society. IEEE, 2013. http://dx.doi.org/10.1109/iecon.2013.6700233.
Pełny tekst źródłaKefalas, Petros, i Ioanna Stamatopoulou. "Using Screencasts to Enhance Logic Programming Skills". W BCI '17: 8th Balkan Conference in Informatics. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3136273.3136286.
Pełny tekst źródłaSu, Yun, Yongqiang Dai i Xiaohong Li. "Logical Model and Verification of Emotion Triggers for BDI Agents". W 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2019. http://dx.doi.org/10.1109/bibm47256.2019.8983137.
Pełny tekst źródłaRaporty organizacyjne na temat "BDI Logics"
Sasao, Tsutomu, i Jon T. Butler. On Bi-Decompositions of Logic Functions. Fort Belvoir, VA: Defense Technical Information Center, maj 1997. http://dx.doi.org/10.21236/ada593005.
Pełny tekst źródłaDopfer, Jaqui. Öffentlichkeitsbeteiligung bei diskursiven Konfliktlösungsverfahren auf regionaler Ebene. Potentielle Ansätze zur Nutzung von Risikokommunikation im Rahmen von e-Government. Sonderforschungsgruppe Institutionenanalyse, 2003. http://dx.doi.org/10.46850/sofia.3933795605.
Pełny tekst źródłaArm, Margus, Karina Egipt, Risto Hansen, Olav Harjo, Marily Hendrikson, Liia Hänni, Raul Kaidro i in. e-Estonia: la e-gobernanza en la práctica. Inter-American Development Bank, luty 2022. http://dx.doi.org/10.18235/0003956.
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