Abstract
The Münster Logic-Imperative Language (Muli) is a constraint-logic object-oriented programming language, suited for the development of applications that interleave constraint-logic search with deterministic, imperative execution. For instance, Muli can generate graph structures of neural networks using non-deterministic search, interleaved with immediate evaluation of each generated network regarding its fitness. Furthermore, it can be used for finding solutions to planning problems. In this paper, we explain and demonstrate how these application problems are solved using Muli.
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Antoy, S., Jost, A.: A new functional-logic compiler for curry: sprite. In: LOPSTR 2016 (2016). https://doi.org/10.1007/978-3-319-63139-4_6
Barto, A.G., Sutton, R.S., Anderson, C.W.: Neuronlike adaptive elements that can solve difficult learning control problems. IEEE Trans. Syst. Man Cybern. 13(5), 834–846 (1983). https://doi.org/10.1109/TSMC.1983.6313077
Kuchen, H. (ed.): LNCS, vol. 6816. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-22531-4
Dageförde, J.C., Kuchen, H.: An operational semantics for constraint-logic imperative programming. In: Seipel, D., Hanus, M., Abreu, S. (eds.) WFLP/WLP/INAP -2017. LNCS (LNAI), vol. 10997, pp. 64–80. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00801-7_5
Dageförde, J.C., Kuchen, H.: A compiler and virtual machine for constraint-logic object-oriented programming with Muli. J. Comput. Lang. 53, 63–78 (2019). https://doi.org/10.1016/j.cola.2019.05.001
Dageförde, J.C., Kuchen, H.: Retrieval of individual solutions from encapsulated search with a potentially infinite search space. In: Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, pp. 1552–1561. Limassol, Cyprus (2019). https://doi.org/10.1145/3297280.3298912
Dageförde, J.C., Teegen, F.: Structured traversal of search trees in constraint-logic object-oriented programming. In: Hofstedt, P., Abreu, S., John, U., Kuchen, H., Seipel, D. (eds.) INAP/WLP/WFLP -2019. LNCS (LNAI), vol. 12057, pp. 199–214. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-46714-2_13
Doyle, J., Meudec, C.: IBIS: an interactive bytecode inspection system, using symbolic execution and constraint logic programming. In: 2nd PPPJ, pp. 55–58 (2003). https://doi.org/10.1145/957289.957307
Hanus, M., Kuchen, H., Moreno-Navarro, J.J.: Curry: a truly functional logic language. In: Workshop on Visions for the Future of Logic Programming (ILPS 1995), pp. 95–107 (1995)
Hara, K., Saito, D., Shouno, H.: Analysis of function of rectified linear unit used in deep learning. In: 2015 International Joint Conference on Neural Networks, pp. 1–8 (2015). https://doi.org/10.1109/IJCNN.2015.7280578
Kingma, D.P., Ba, J.L.: Adam: a method for stochastic optimization. In: 3rd International Conference on Learning Representations, ICLR 2015 - Conference Track Proceedings, pp. 1–15 (2015). https://arxiv.org/abs/1412.6980
Kuchcinski, K.: Constraints-driven scheduling and resource assignment. ACM Trans. Des. Autom. Electron. Syst. 8(3), 355–383 (2003). https://doi.org/10.1145/785411.785416
Lux, W., Kuchen, H.: An efficient abstract machine for curry. In: Beiersdörfer, K., Engels, G., Schäfer, W. (eds.) Informatik 1999. Informatik aktuell, pp. 390–399. Springer, Heidelberg (1999). https://doi.org/10.1007/978-3-662-01069-3_58
Majchrzak, T.A., Kuchen, H.: Logic Java: combining object-oriented and logic programming. In: WFLP, pp. 122–137 (2011). https://doi.org/10.1007/978-3-642-22531-4_8
McCabe, F.G.: Logic and Objects. Prentice-Hall International Series in Computer Science, Prentice Hall (1992)
Moss, C.: Prolog++ - the power of object-oriented and logic programming. International Series in Logic Programming, Addison-Wesley (1994)
OpenAI: CartPole-v1 (2020). https://gym.openai.com/envs/CartPole-v1/
Palnitkar, R.M., Cannady, J.: A review of adaptive neural networks. In: IEEE SoutheastCon 2004. Proceedings, pp. 38–47 (2004). https://doi.org/10.1109/SECON.2004.1287896
Paszke, A., et al.: PyTorch: an imperative style, high-performance deep learning library. In: Wallach, H., Larochelle, H., Beygelzimer, A., Alché-Buc, F., Fox, E., Garnett, R. (eds.) Advances in Neural Information Processing Systems, vol. 32, pp. 8024–8035. Curran Associates, Inc. (2019)
Prud’homme, C., Fages, J.G., Lorca, X.: Choco documentation. TASC - LS2N CNRS UMR 6241, COSLING S.A.S. (2017). https://www.choco-solver.org
Renshaw, D.: Seer: symbolic execution engine for rust (2018). https://github.com/dwrensha/seer
Scott, R.: A Guide to Artificial Intelligence with Visual Prolog. Outskirts Press, Parker, Colorado (2010)
Shapiro, E., Takeuchi, A.: Object oriented programming in concurrent prolog. New Gener. Comput. 1(1), 25–48 (1983). https://doi.org/10.1007/BF03037020
Srivastava, N., Hinton, G.E., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15, 1929–1958 (2014)
Beckert, B., Hähnle, R. (eds.): LNCS, vol. 4966. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-79124-9
Van Roy, P., Brand, P., Duchier, D., Haridi, S., Schulte, C., Henz, M.: Logic programming in the context of multiparadigm programming: the Oz experience. Theory Pract. Log. Program. 3(6), 717–763 (2003). https://doi.org/10.1017/S1471068403001741
Warren, D.H.D.: An abstract prolog instruction set. Tech. rep., SRI International, Menlo Park (1983)
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Dageförde, J.C., Kuchen, H. (2023). Applications of Muli: Solving Practical Problems with Constraint-Logic Object-Oriented Programming. In: Lopez-Garcia, P., Gallagher, J.P., Giacobazzi, R. (eds) Analysis, Verification and Transformation for Declarative Programming and Intelligent Systems. Lecture Notes in Computer Science, vol 13160. Springer, Cham. https://doi.org/10.1007/978-3-031-31476-6_5
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