{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T12:27:50Z","timestamp":1775737670320,"version":"3.50.1"},"reference-count":78,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T00:00:00Z","timestamp":1755734400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T00:00:00Z","timestamp":1755734400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100007601","name":"Horizon 2020","doi-asserted-by":"publisher","award":["101070381"],"award-info":[{"award-number":["101070381"]}],"id":[{"id":"10.13039\/501100007601","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100021856","name":"Ministero dell\u2019Universit\u00e0 e della Ricerca","doi-asserted-by":"publisher","award":["PE0000013-FAIR"],"award-info":[{"award-number":["PE0000013-FAIR"]}],"id":[{"id":"10.13039\/501100021856","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Prog Artif Intell"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>This work presents a novel architecture for an open-ended learning system that integrates intrinsic motivation (IM) and classical planning to enable agents continuously learn and improve their knowledge over time in an unsupervised fashion. The main goal is to allow the agent to autonomously distill its experience into Probabilistic Planning Domain Definition Language (PPDDL) terms, thereby making causal relationships explicit and supporting automated planning. Starting with a virtually empty set of predefined tasks or goals, the agent harnesses intrinsic motivation to explore the environment autonomously, continuously using and enriching the high-level knowledge acquired through its experience in a virtuous cycle. Experimental evaluation in the Treasure Game domain demonstrates the effectiveness of the proposed approach: starting with only a small set of primitive actions, we show how an agent can autonomously build and refine a high-level representation of the environment. Planning-based strategies grounded in this representation significantly outperform uninformed exploration by reaching intermediate sub-goals more efficiently and substantially reducing the time required to achieve the final objective.<\/jats:p>","DOI":"10.1007\/s13748-025-00394-9","type":"journal-article","created":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T13:42:28Z","timestamp":1755783748000},"page":"117-138","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Synthesizing Evolving Symbolic Representations for Autonomous Systems"],"prefix":"10.1007","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6530-318X","authenticated-orcid":false,"given":"Gabriele","family":"Sartor","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4370-7156","authenticated-orcid":false,"given":"Angelo","family":"Oddi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2420-4713","authenticated-orcid":false,"given":"Riccardo","family":"Rasconi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8748-9632","authenticated-orcid":false,"given":"Vieri Giuliano","family":"Santucci","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0434-4850","authenticated-orcid":false,"given":"Rosa","family":"Meo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,8,21]]},"reference":[{"issue":"1","key":"394_CR1","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/S0004-3702(01)00129-1","volume":"134","author":"M Campbell","year":"2002","unstructured":"Campbell, M., Hoane, A.J., Hsu, F.H.: Deep Blue. Artif. Intell. 134(1), 57\u201383 (2002). https:\/\/doi.org\/10.1016\/S0004-3702(01)00129-1","journal-title":"Artif. Intell."},{"issue":"6419","key":"394_CR2","doi-asserted-by":"publisher","first-page":"1140","DOI":"10.1126\/science.aar6404","volume":"362","author":"D Silver","year":"2018","unstructured":"Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., Guez, A., et al.: A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play. Science 362(6419), 1140\u20131144 (2018)","journal-title":"Science"},{"issue":"7587","key":"394_CR3","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1038\/nature16961","volume":"529","author":"D Silver","year":"2016","unstructured":"Silver, D., Huang, A., Maddison, C.J., Guez, A., Sifre, L., Van Den Driessche, G., et al.: Mastering the game of Go with deep neural networks and tree search. Nature 529(7587), 484\u2013489 (2016)","journal-title":"Nature"},{"issue":"7676","key":"394_CR4","doi-asserted-by":"publisher","first-page":"354","DOI":"10.1038\/nature24270","volume":"550","author":"D Silver","year":"2017","unstructured":"Silver, D., Schrittwieser, J., Simonyan, K., Antonoglou, I., Huang, A., Guez, A., et al.: Mastering the game of go without human knowledge. Nature 550(7676), 354\u2013359 (2017)","journal-title":"Nature"},{"key":"394_CR5","unstructured":"Oh, J., Guo, X., Lee, H., Lewis, R.L., Singh, S.: Action-conditional video prediction using deep networks in atari games. Adv. Neural. Inf. Process. Syst. 28, (2015)"},{"key":"394_CR6","unstructured":"Berner, C., Brockman, G., Chan, B., Cheung, V., D\u0119biak, P., Dennison, C., et al. Dota 2 with large scale deep reinforcement learning. arXiv preprint arXiv:1912.06680. 2019"},{"issue":"2","key":"394_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3301273","volume":"3","author":"W Koch","year":"2019","unstructured":"Koch, W., Mancuso, R., West, R., Bestavros, A.: Reinforcement learning for UAV attitude control. ACM Transactions on Cyber-Physical Systems. 3(2), 1\u201321 (2019)","journal-title":"ACM Transactions on Cyber-Physical Systems."},{"key":"394_CR8","doi-asserted-by":"crossref","unstructured":"Nguyen, H., La, H.: Review of deep reinforcement learning for robot manipulation. In: 2019 Third IEEE International Conference on Robotic Computing (IRC). IEEE; p. 590\u2013595 (2019)","DOI":"10.1109\/IRC.2019.00120"},{"issue":"4\u20135","key":"394_CR9","doi-asserted-by":"publisher","first-page":"698","DOI":"10.1177\/0278364920987859","volume":"40","author":"J Ibarz","year":"2021","unstructured":"Ibarz, J., Tan, J., Finn, C., Kalakrishnan, M., Pastor, P., Levine, S.: How to train your robot with deep reinforcement learning: lessons we have learned. The International Journal of Robotics Research. 40(4\u20135), 698\u2013721 (2021)","journal-title":"The International Journal of Robotics Research."},{"issue":"7836","key":"394_CR10","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1038\/s41586-020-2939-8","volume":"588","author":"MG Bellemare","year":"2020","unstructured":"Bellemare, M.G., Candido, S., Castro, P.S., Gong, J., Machado, M.C., Moitra, S., et al.: Autonomous navigation of stratospheric balloons using reinforcement learning. Nature 588(7836), 77\u201382 (2020)","journal-title":"Nature"},{"key":"394_CR11","volume-title":"Reinforcement learning: An introduction","author":"RS Sutton","year":"2018","unstructured":"Sutton, R.S., Barto, A.G.: Reinforcement learning: An introduction. MIT press (2018)"},{"key":"394_CR12","volume-title":"Deep learning","author":"Y Bengio","year":"2017","unstructured":"Bengio, Y., Goodfellow, I., Courville, A.: Deep learning, vol. 1. MIT press Cambridge, MA, USA (2017)"},{"issue":"2","key":"394_CR13","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1037\/h0061616","volume":"46","author":"RA Butler","year":"1953","unstructured":"Butler, R.A.: Discrimination learning by rhesus monkeys to visual-exploration motivation. J. Comp. Physiol. Psychol. 46(2), 95 (1953)","journal-title":"J. Comp. Physiol. Psychol."},{"issue":"4","key":"394_CR14","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1037\/h0058114","volume":"43","author":"HF Harlow","year":"1950","unstructured":"Harlow, H.F.: Learning and satiation of response in intrinsically motivated complex puzzle performance by monkeys. J. Comp. Physiol. Psychol. 43(4), 289 (1950)","journal-title":"J. Comp. Physiol. Psychol."},{"issue":"1","key":"394_CR15","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1037\/h0054833","volume":"47","author":"KC Montgomery","year":"1954","unstructured":"Montgomery, K.C.: The role of the exploratory drive in learning. J. Comp. Physiol. Psychol. 47(1), 60 (1954)","journal-title":"J. Comp. Physiol. Psychol."},{"issue":"1","key":"394_CR16","first-page":"68","volume":"41","author":"DE Berlyne","year":"1950","unstructured":"Berlyne, D.E.: Novelty and curiosity as determinants of exploratory behaviour. Br. J. Psychol. 41(1), 68 (1950)","journal-title":"Br. J. Psychol."},{"issue":"3731","key":"394_CR17","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1126\/science.153.3731.25","volume":"153","author":"DE Berlyne","year":"1966","unstructured":"Berlyne, D.E.: Curiosity and Exploration: Animals spend much of their time seeking stimuli whose significance raises problems for psychology. Science 153(3731), 25\u201333 (1966)","journal-title":"Science"},{"issue":"1","key":"394_CR18","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1006\/ceps.1999.1020","volume":"25","author":"RM Ryan","year":"2000","unstructured":"Ryan, R.M., Deci, E.L.: Intrinsic and Extrinsic Motivations: Classic Definitions and New Directions. Contemp. Educ. Psychol. 25(1), 54\u20136 (2000). https:\/\/doi.org\/10.1006\/ceps.1999.1020","journal-title":"Contemp. Educ. Psychol."},{"issue":"5","key":"394_CR19","doi-asserted-by":"publisher","first-page":"660","DOI":"10.1016\/j.neubiorev.2009.08.006","volume":"34","author":"E D\u00fczel","year":"2010","unstructured":"D\u00fczel, E., Bunzeck, N., Guitart-Masip, M., D\u00fczel, S.: NOvelty-related motivation of anticipation and exploration by dopamine (NOMAD): implications for healthy aging. Neuroscience & Biobehavioral Reviews. 34(5), 660\u2013669 (2010)","journal-title":"Neuroscience & Biobehavioral Reviews."},{"issue":"3","key":"394_CR20","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1038\/nrn1052","volume":"4","author":"C Ranganath","year":"2003","unstructured":"Ranganath, C., Rainer, G.: Neural mechanisms for detecting and remembering novel events. Nat. Rev. Neurosci. 4(3), 193\u2013202 (2003)","journal-title":"Nat. Rev. Neurosci."},{"issue":"12","key":"394_CR21","doi-asserted-by":"publisher","first-page":"967","DOI":"10.1038\/nrn2022","volume":"7","author":"P Redgrave","year":"2006","unstructured":"Redgrave, P., Gurney, K.: The short-latency dopamine signal: a role in discovering novel actions? Nat. Rev. Neurosci. 7(12), 967\u2013975 (2006)","journal-title":"Nat. Rev. Neurosci."},{"key":"394_CR22","doi-asserted-by":"publisher","first-page":"115","DOI":"10.3389\/fnbot.2019.00115","volume":"13","author":"VG Santucci","year":"2020","unstructured":"Santucci, V.G., Oudeyer, P.Y., Barto, A., Baldassarre, G.: Intrinsically motivated open-ended learning in autonomous robots. Front. Neurorobot. 13, 115 (2020)","journal-title":"Front. Neurorobot."},{"issue":"2","key":"394_CR23","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1109\/TEVC.2006.890271","volume":"11","author":"PY Oudeyer","year":"2007","unstructured":"Oudeyer, P.Y., Kaplan, F., Hafner, V.: Intrinsic motivation systems for autonomous mental development. IEEE Trans. Evol. Comput. 11(2), 265\u2013286 (2007)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"394_CR24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-32375-1","volume-title":"Intrinsically Motivated Learning in Natural and Artificial Systems","author":"G Baldassarre","year":"2013","unstructured":"Baldassarre, G., Mirolli, M.: Intrinsically Motivated Learning in Natural and Artificial Systems. Springer Science & Business Media (2013)"},{"key":"394_CR25","doi-asserted-by":"publisher","first-page":"25","DOI":"10.3389\/fnbot.2013.00025","volume":"7","author":"M Frank","year":"2014","unstructured":"Frank, M., Leitner, J., Stollenga, M., F\u00f6rster, A., Schmidhuber, J.: Curiosity driven reinforcement learning for motion planning on humanoids. Front. Neurorobot. 7, 25 (2014)","journal-title":"Front. Neurorobot."},{"key":"394_CR26","unstructured":"Bellemare, M., Srinivasan, S., Ostrovski, G., Schaul, T., Saxton, D., Munos, R.: Unifying count-based exploration and intrinsic motivation. Advances in neural information processing systems. 29 (2016)"},{"issue":"3","key":"394_CR27","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1109\/TCDS.2016.2538961","volume":"8","author":"VG Santucci","year":"2016","unstructured":"Santucci, V.G., Baldassarre, G., Mirolli, M.: GRAIL: A Goal-Discovering Robotic Architecture for Intrinsically-Motivated Learning. IEEE Transactions on Cognitive and Developmental Systems. 8(3), 214\u201323 (2016). https:\/\/doi.org\/10.1109\/TCDS.2016.2538961","journal-title":"IEEE Transactions on Cognitive and Developmental Systems."},{"key":"394_CR28","unstructured":"Colas, C., Fournier, P., Chetouani, M., Sigaud, O., Oudeyer, P. Y.: CURIOUS: intrinsically motivated modular multi-goal reinforcement learning. In: International conference on machine learning. PMLR; p. 1331\u20131340 (2019)"},{"key":"394_CR29","unstructured":"Blaes, S., Vlastelica Pogan\u010di\u0107, M., Zhu, J., Martius, G.: Control what you can: Intrinsically motivated task-planning agent. Advances in Neural Information Processing Systems. 32 (2019)"},{"key":"394_CR30","unstructured":"Sigaud, O., Baldassarre, G., Colas, C., Doncieux, S., Duro, R., Perrin-Gilbert, N., et al. A Definition of Open-Ended Learning Problems for Goal-Conditioned Agents. arXiv preprint arXiv:2311.00344. (2023)"},{"key":"394_CR31","unstructured":"Baldassarre, G., Duro, R. J., Cartoni, E., Khamassi, M., Romero, A., Santucci, V. G.: Purpose for Open-Ended Learning Robots: A Computational Taxonomy, Definition, and Operationalisation. arXiv preprint arXiv:2403.02514. (2024)"},{"key":"394_CR32","unstructured":"Singh, S., Barto, A. G., Chentanez, N.: Intrinsically Motivated Reinforcement Learning. In: Proceedings of the 17th International Conference on Neural Information Processing Systems. NIPS\u201904. Cambridge, MA, USA: MIT Press; p. 1281-1288 (2004)"},{"key":"394_CR33","unstructured":"Forestier, S., Portelas, R., Mollard, Y., Oudeyer, P. Y.: Intrinsically motivated goal exploration processes with automatic curriculum learning. arXiv preprint arXiv:1708.02190. (2017);"},{"key":"394_CR34","doi-asserted-by":"crossref","unstructured":"Romero, A., Baldassarre, G., Duro, R. J., Santucci, V. G.: Autonomous learning of multiple curricula with non-stationary interdependencies. In: 2022 IEEE International Conference on Development and Learning (ICDL). IEEE; p. 272\u2013279 (2022)","DOI":"10.1109\/ICDL53763.2022.9962200"},{"key":"394_CR35","doi-asserted-by":"crossref","unstructured":"Bengio, Y., Louradour, J., Collobert, R., Weston, J.: Curriculum learning. In: Proceedings of the 26th annual international conference on machine learning; p. 41\u201348 (2009)","DOI":"10.1145\/1553374.1553380"},{"key":"394_CR36","unstructured":"Machado, M. C., Bellemare, M. G., Bowling, M.: A laplacian framework for option discovery in reinforcement learning. arXiv preprint arXiv:1703.00956. (2017)"},{"key":"394_CR37","unstructured":"Oddi, A., Rasconi, R., Santucci, V. G., Sartor, G., Cartoni, E., Mannella, F., et al. Integrating open-ended learning in the sense-plan-act robot control paradigm. In: ECAI 2020. IOS Press; p. 2417\u20132424 (2020)"},{"key":"394_CR38","unstructured":"Sartor, G., Zollo, D., Mayer, M. C., Oddi, A., Rasconi, R., Santucci, V. G.: Autonomous Generation of Symbolic Knowledge via Option Discovery. In: Proceedings of the 9th Italian workshop on Planning and Scheduling (IPS\u201921) and the 28th International Workshop on \"Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion\" (RCRA\u201921). vol. 3065 of CEUR Workshop Proceedings. CEUR-WS.org; (2021)"},{"key":"394_CR39","doi-asserted-by":"crossref","unstructured":"Sartor, G., Zollo, D., Cialdea Mayer, M., Oddi, A., Rasconi, R., Santucci, V. G.: Option Discovery for Autonomous Generation of Symbolic Knowledge. In: International Conference of the Italian Association for Artificial Intelligence. Springer; p. 153\u2013167 (2022)","DOI":"10.1007\/978-3-031-08421-8_11"},{"issue":"1","key":"394_CR40","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1023\/A:1022140919877","volume":"13","author":"AG Barto","year":"2003","unstructured":"Barto, A.G., Mahadevan, S.: Recent advances in hierarchical reinforcement learning. Discrete event dynamic systems. 13(1), 41\u201377 (2003)","journal-title":"Discrete event dynamic systems."},{"key":"394_CR41","unstructured":"Konidaris, G., Barto, A. G.: Skill discovery in continuous reinforcement learning domains using skill chaining. In: Advances in neural information processing systems; p. 1015\u20131023 (2009)"},{"key":"394_CR42","doi-asserted-by":"crossref","unstructured":"Niel, R., Wiering, M. A.: Hierarchical Reinforcement Learning for Playing a Dynamic Dungeon Crawler Game. In: 2018 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE; p. 1159\u20131166 (2018)","DOI":"10.1109\/SSCI.2018.8628914"},{"key":"394_CR43","unstructured":"Rafati, J., Noelle, D. C.: Unsupervised Methods For Subgoal Discovery During Intrinsic Motivation in Model-Free Hierarchical Reinforcement Learning. In: KEG@ AAAI; p. 17\u201325 (2019)"},{"key":"394_CR44","first-page":"20516","volume":"34","author":"S Parisi","year":"2021","unstructured":"Parisi, S., Dean, V., Pathak, D., Gupta, A.: Interesting object, curious agent: Learning task-agnostic exploration. Adv. Neural. Inf. Process. Syst. 34, 20516\u201320530 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"394_CR45","doi-asserted-by":"crossref","unstructured":"Romero, A., Baldassarre, G., Duro, R. J., Santucci, V. G.: Analysing autonomous open-ended learning of skills with different interdependent subgoals in robots. In: 2021 20th International Conference on Advanced Robotics (ICAR). IEEE; p. 646\u2013651 (2021)","DOI":"10.1109\/ICAR53236.2021.9659371"},{"key":"394_CR46","unstructured":"Bagaria, A., Senthil, J. K., Konidaris, G.: Skill Discovery for Exploration and Planning using Deep Skill Graphs. In: Meila M, Zhang T, editors. Proceedings of the 38th International Conference on Machine Learning. vol. 139 of Proceedings of Machine Learning Research. PMLR; p. 521\u2013531 (2021) Available from: https:\/\/proceedings.mlr.press\/v139\/bagaria21a.html"},{"key":"394_CR47","first-page":"29861","volume":"34","author":"V Veeriah","year":"2021","unstructured":"Veeriah, V., Zahavy, T., Hessel, M., Xu, Z., Oh, J., Kemaev, I., et al.: Discovery of options via meta-learned subgoals. Adv. Neural. Inf. Process. Syst. 34, 29861\u201329873 (2021)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"394_CR48","volume-title":"Automated Planning: Theory & Practice","author":"D Nau","year":"2004","unstructured":"Nau, D., Ghallab, M., Traverso, P.: Automated Planning: Theory & Practice. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA (2004)"},{"key":"394_CR49","volume-title":"Artificial intelligence a modern approach","author":"SJ Russell","year":"2010","unstructured":"Russell, S.J.: Artificial intelligence a modern approach. Pearson Education, Inc. (2010)"},{"key":"394_CR50","doi-asserted-by":"crossref","unstructured":"Chitnis, R., Silver, T., Tenenbaum, J. B., Kaelbling, L. P., Lozano-P\u00e9rez, T.: Glib: Efficient exploration for relational model-based reinforcement learning via goal-literal babbling. In: Proceedings of the AAAI Conference on Artificial Intelligence. 35, 11782\u201311791 (2021)","DOI":"10.1609\/aaai.v35i13.17400"},{"key":"394_CR51","doi-asserted-by":"crossref","unstructured":"Mikita, H., Azuma, H., Kakiuchi, Y., Okada, K., Inaba, M.: Interactive symbol generation of task planning for daily assistive robot. In: 2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012). IEEE; p. 698\u2013703 (2012)","DOI":"10.1109\/HUMANOIDS.2012.6651596"},{"key":"394_CR52","doi-asserted-by":"crossref","unstructured":"Rodr\u00edguez-Lera, F. J., Mart\u00edn-Rico, F., Mateli\u00e1n-Olivera, V.: Generating symbolic representation from sensor data: inferring knowledge in robotics competitions. In: 2018 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC). IEEE; p. 261\u2013266 (2018)","DOI":"10.1109\/ICARSC.2018.8374193"},{"key":"394_CR53","unstructured":"Ganapini, M. B., Campbell, M., Fabiano, F., Horesh, L., Lenchner, J., Loreggia, A., et al. Combining Fast and Slow Thinking for Human-like and Efficient Navigation in Constrained Environments. arXiv preprint arXiv:2201.07050. (2022)"},{"key":"394_CR54","unstructured":"Garnelo, M., Arulkumaran, K., Shanahan, M.: Towards deep symbolic reinforcement learning. arXiv preprint arXiv:1609.05518. (2016)"},{"key":"394_CR55","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.cobeha.2018.12.010","volume":"29","author":"M Garnelo","year":"2019","unstructured":"Garnelo, M., Shanahan, M.: Reconciling deep learning with symbolic artificial intelligence: representing objects and relations. Curr. Opin. Behav. Sci. 29, 17\u201323 (2019). https:\/\/doi.org\/10.1016\/j.cobeha.2018.12.010. (SI: 29: Artificial Intelligence (2019))","journal-title":"Curr. Opin. Behav. Sci."},{"key":"394_CR56","doi-asserted-by":"crossref","unstructured":"Amado, L., Pereira, R. F., Aires, J., Magnaguagno, M., Granada, R., Meneguzzi, F.: Goal recognition in latent space. In: 2018 International Joint Conference on Neural Networks (IJCNN). IEEE; p. 1\u20138 (2018)","DOI":"10.1109\/IJCNN.2018.8489653"},{"key":"394_CR57","doi-asserted-by":"publisher","unstructured":"Asai, M., Fukunaga, A.: Classical Planning in Deep Latent Space: Bridging the Subsymbolic-Symbolic Boundary. Proceedings of the AAAI Conference on Artificial Intelligence. 32(1), (2018). https:\/\/doi.org\/10.1609\/aaai.v32i1.12077","DOI":"10.1609\/aaai.v32i1.12077"},{"key":"394_CR58","doi-asserted-by":"crossref","unstructured":"Asai, M.: Unsupervised grounding of plannable first-order logic representation from images. In: Proceedings of the International Conference on Automated Planning and Scheduling. vol.\u00a029; . p. 583\u2013591 (2019)","DOI":"10.1609\/icaps.v29i1.3525"},{"key":"394_CR59","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1613\/jair.5575","volume":"61","author":"G Konidaris","year":"2018","unstructured":"Konidaris, G., Kaelbling, L.P., Lozano-Perez, T.: From skills to symbols: Learning symbolic representations for abstract high-level planning. Journal of Artificial Intelligence Research. 61, 215\u2013289 (2018)","journal-title":"Journal of Artificial Intelligence Research."},{"key":"394_CR60","unstructured":"Ghallab, M., Howe, A., Knoblock, C., Mcdermott, D., Ram, A., Veloso, M., et al.: PDDL\u2014The Planning Domain Definition Language. Available from: http:\/\/citeseerx.ist.psu.edu\/viewdoc\/summary?doi=10.1.1.37.212"},{"key":"394_CR61","unstructured":"Oddi, A., Rasconi, R., Santucci, V. G., Sartor, G., Cartoni, E., Mannella, F., Baldassarre, G. (2020). An intrinsically motivated planning architecture for curiosity-driven robots. 6th Italian Workshop on Artificial Intelligence and Robotics, AIRO 2019 (Vol. 2594, pp. 19\u201324). CEUR-WS."},{"issue":"1","key":"394_CR62","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1016\/S0004-3702(99)00052-1","volume":"112","author":"RS Sutton","year":"1999","unstructured":"Sutton, R.S., Precup, D., Singh, S.: Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning. Artif. Intell. 112(1), 181\u2013211 (1999)","journal-title":"Artif. Intell."},{"key":"394_CR63","unstructured":"Younes, H. L., Littman, M. L.: PPDDL1. 0: An extension to PDDL for expressing planning domains with probabilistic effects. Techn Rep CMU-CS-04-162. 2:99 (2004)"},{"issue":"3","key":"394_CR64","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1109\/TAMD.2010.2056368","volume":"2","author":"J Schmidhuber","year":"2010","unstructured":"Schmidhuber, J.: Formal theory of creativity, fun, and intrinsic motivation (1990\u20132010). IEEE Trans. Auton. Ment. Dev. 2(3), 230\u2013247 (2010)","journal-title":"IEEE Trans. Auton. Ment. Dev."},{"key":"394_CR65","unstructured":"Santucci, V. G., Baldassarre, G., Mirolli, M.: Biological Cumulative Learning through Intrinsic Motivations: A Simulated Robotic Study on the Development of Visually-Guided Reaching. In: EpiRob. Citeseer; (2010)"},{"key":"394_CR66","doi-asserted-by":"publisher","first-page":"907","DOI":"10.3389\/fpsyg.2013.00907","volume":"4","author":"A Barto","year":"2013","unstructured":"Barto, A., Mirolli, M., Baldassarre, G.: Novelty or surprise? Front. Psychol. 4, 907 (2013)","journal-title":"Front. Psychol."},{"key":"394_CR67","doi-asserted-by":"crossref","unstructured":"Mirolli, M., Baldassarre, G.: Functions and mechanisms of intrinsic motivations: The knowledge versus competence distinction. Intrinsically motivated learning in natural and artificial systems. p. 49\u201372 (2013)","DOI":"10.1007\/978-3-642-32375-1_3"},{"key":"394_CR68","unstructured":"Oudeyer, P. Y., Kaplan, F.: What is intrinsic motivation? A typology of computational approaches. Frontiers in neurorobotics. p. 6 (2009)"},{"key":"394_CR69","unstructured":"Ester, M., Kriegel, H. P., Sander, J., Xu, X.: A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. In: Proceedings of the Second International Conference on Knowledge Discovery and Data Mining. KDD\u201996. AAAI Press; p. 226-231 (1996)"},{"issue":"3","key":"394_CR70","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1023\/A:1022627411411","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes, C., Vapnik, V.: Support-Vector Networks. Mach. Learn. 20(3), 273\u2013297 (1995)","journal-title":"Mach. Learn."},{"issue":"3","key":"394_CR71","doi-asserted-by":"publisher","first-page":"832","DOI":"10.1214\/aoms\/1177728190","volume":"27","author":"M Rosenblatt","year":"1956","unstructured":"Rosenblatt, M.: Remarks on Some Nonparametric Estimates of a Density Function. Ann. Math. Stat. 27(3), 832\u2013837 (1956)","journal-title":"Ann. Math. Stat."},{"issue":"3","key":"394_CR72","doi-asserted-by":"publisher","first-page":"1065","DOI":"10.1214\/aoms\/1177704472","volume":"33","author":"E Parzen","year":"1962","unstructured":"Parzen, E.: On Estimation of a Probability Density Function and Mode. Ann. Math. Stat. 33(3), 1065\u20131076 (1962)","journal-title":"Ann. Math. Stat."},{"issue":"3","key":"394_CR73","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1109\/TAMD.2010.2062511","volume":"2","author":"M Rolf","year":"2010","unstructured":"Rolf, M., Steil, J.J., Gienger, M.: Goal babbling permits direct learning of inverse kinematics. IEEE Trans. Auton. Ment. Dev. 2(3), 216\u2013229 (2010)","journal-title":"IEEE Trans. Auton. Ment. Dev."},{"key":"394_CR74","unstructured":"Ecoffet, A., Huizinga, J., Lehman, J., Stanley, K. O., Clune, J.: Go-explore: a new approach for hard-exploration problems. arXiv preprint arXiv:1901.10995. (2019)"},{"key":"394_CR75","doi-asserted-by":"crossref","unstructured":"Bharadhwaj, H., Garg, A., Shkurti, F.: Leaf: Latent exploration along the frontier. In: 2021 IEEE International Conference on Robotics and Automation (ICRA). IEEE; p. 677\u2013684 (2021)","DOI":"10.1109\/ICRA48506.2021.9560922"},{"key":"394_CR76","doi-asserted-by":"crossref","unstructured":"Jin, B., Xu, X.: Wholesale price forecasts of green grams using the neural network. Asian Journal of Economics and Banking. (2024);(ahead-of-print)","DOI":"10.1108\/AJEB-01-2024-0007"},{"issue":"15","key":"394_CR77","doi-asserted-by":"publisher","first-page":"8693","DOI":"10.1007\/s00521-024-09531-2","volume":"36","author":"B Jin","year":"2024","unstructured":"Jin, B., Xu, X.: Forecasting wholesale prices of yellow corn through the Gaussian process regression. Neural Comput. Appl. 36(15), 8693\u20138710 (2024)","journal-title":"Neural Comput. Appl."},{"key":"394_CR78","unstructured":"James, S., Rosman, B., Konidaris, G.: Autonomous learning of object-centric abstractions for high-level planning. In: International Conference on Learning Representations; (2021)"}],"container-title":["Progress in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13748-025-00394-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13748-025-00394-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13748-025-00394-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T14:07:19Z","timestamp":1771596439000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13748-025-00394-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,21]]},"references-count":78,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,3]]}},"alternative-id":["394"],"URL":"https:\/\/doi.org\/10.1007\/s13748-025-00394-9","relation":{},"ISSN":["2192-6352","2192-6360"],"issn-type":[{"value":"2192-6352","type":"print"},{"value":"2192-6360","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,21]]},"assertion":[{"value":"25 September 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 July 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 August 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflicts of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of Interest"}}]}}