RPHMS104A - Robotic Prototype Concept (Preprint).pdf

<b>Abstract</b>This paper introduces the RPHMS104A model (Robotic Prototype with Human Mimicry Abilities - 104 Algorithms), a framework for the progressive development of artificial systems capable of emulating human cognitive-behavioral functions. The system is stratified in five ascending levels of algorithmic complexity, from HMS-1 to HMS-5, culminating in the simulation of "Very Complex Skills". RPHMS104A integrates advanced computational techniques, machine learning (ML), deep neural networks (DNNs), and principles from quantum computing and cognitive robotics, proposing a paradigm shift toward a unified computational theory for human-like artificial intelligence.____________________<br><b>References</b>Biamonte, J., Wittek, P., Pancotti, N., Rebentrost, P., Wiebe, N., &amp; Lloyd, S. (2017). Quantum machine learning. Nature, 549(7671), 195–202. [https://doi.org/10.1038/nature23474](https://doi.org/10.1038/nature23474)Garcez, A. d., Lamb, L. C., &amp; Gabbay, D. M. (2019). Neural-symbolic cognitive reasoning. Springer. [https://doi.org/10.1007/978-3-030-03347-3](https://doi.org/10.1007/978-3-030-03347-3)Goertzel, B., &amp; Pennachin, C. (Eds.). (2007). Artificial general intelligence. Springer. [https://doi.org/10.1007/978-3-540-68677-4](https://doi.org/10.1007/978-3-540-68677-4)Goodfellow, I., et al. (2014). Generative adversarial nets. Advances in Neural Information Processing Systems, 27. https://papers.nips.cc/paper\_files/paper/2014/hash/5ca3e9b122f61f8f06494c97b1afccf3-Abstract.html](https://papers.nips.cc/paper_files/paper/2014/hash/5ca3e9b122f61f8f06494c97b1afccf3-Abstract.html)Hawkins, J., &amp; Blakeslee, S. (2004). On Intelligence. Times Books.Hassabis, D., Kumaran, D., Summerfield, C., &amp; Botvinick, M. (2017). Neuroscience-inspired artificial intelligence. Neuron, 95(2), 245–258. [https://doi.org/10.1016/j.neuron.2017.06.011LeCun, Y., Bengio, Y., &amp; Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444. [https://doi.org/10.1038/nature14539](https://doi.org/10.1038/nature14539)Preskill, J. (2018). Quantum computing in the NISQ era and beyond. Quantum, 2, 79. [https://doi.org/10.22331/q-2018-08-06-79](https://doi.org/10.22331/q-2018-08-06-79)Sun, R. (2004). Desiderata for cognitive architectures. Philosophical Psychology, 17(3), 341–373. [https://doi.org/10.1080/0951508042000286721](https://doi.org/10.1080/0951508042000286721)Vaswani, A., et al. (2017). Attention is all you need. Advances in Neural Information Processing Systems, 30. [https://papers.nips.cc/paper\_files/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html](https://papers.nips.cc/paper_files/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html)<br><br>